Image processing apparatus and method, and image pickup apparatus

ABSTRACT

An object of the present invention is to enable the detection of a mixture ratio indicating the mixture state of a plurality of objects, such as a background image and a moving object image. A normal-equation adder  541  extracts mixed pixel data according to a motion, and also extracts background pixel data corresponding to the mixed pixel data so as to generate relational expressions for a designated pixel. A normal-equation calculator  542  detects the mixture ratio indicating the mixture state of the objects based on the relational expressions. The normal-equation adder  541  generates the plurality of relational expressions based on a first approximation in which foreground object components change substantially linearly, and a second approximation in which the mixture ratio changes substantially linearly. The present invention is applicable to a signal processing apparatus for processing images.

TECHNICAL FIELD

The present invention relates to image processing apparatuses andmethods, and image-capturing apparatuses, and more particularly, to animage processing apparatus and method, and an image-capturing apparatusin which a difference between a signal detected by a sensor and the realworld is taken into consideration.

BACKGROUND ART

A technique for detecting incidents occurring in the real world by asensor and for processing sampled data output from the image sensor iswidely used.

For example, motion blur occurs in an image obtained by capturing anobject moving in front of a predetermined stationary background with avideo camera if the moving speed is relatively high.

However, when an object is moving in front of a stationary background,not only does motion blur caused by the mixture of the moving objectitself occur, but also the mixture of the background image and theobject image occurs. Hitherto, it has not been considered to detect themixture state of the background image and the moving object.

DISCLOSURE OF INVENTION

The present invention has been made in view of the above-describedbackground. Accordingly, it is an object of the present invention tomake it possible to detect the mixture ratio indicating the mixturestate of a plurality of objects, such as a background image and a movingobject image.

A first image processing apparatus of the present invention includes:relational-expression generating means for extracting, in correspondencewith a designated pixel of a designated frame of image data, mixed pixeldata, which is pixel data, in which a plurality of objects contained inthe image data are mixed, from the designated frame and a peripheralframe around the designated frame in accordance with a motion of aforeground object which forms a foreground of the plurality of objects,and also for extracting, in correspondence with the mixed pixel data,background pixel data, which is the pixel data, corresponding to abackground object which forms a background of the plurality of objects,the background pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and mixture-ratio detectionmeans for detecting a mixture ratio indicating a mixture state of theplurality of objects in the real world concerning the designated pixelbased on the relational expressions. The relational-expressiongenerating means generates the plurality of relational expressions basedon a first approximation in which components of the foreground objectcontained in the mixed pixel data change substantially linearly withrespect to the positions of the pixels, and a second approximation inwhich the mixture ratio of the mixed pixel data extracted from thedesignated frame changes substantially linearly with respect to thepositions of the pixels.

The image processing apparatus may further include foreground/backgroundseparation means for separating the image data into a foreground objectimage consisting of only the foreground object components which form theforeground object in the image data and a background object imageconsisting of only background object components which form thebackground object in the image data based on the mixture ratiocorresponding to the designated pixel.

The mixture-ratio detection means may detect the mixture ratio bysolving the plurality of relational expressions according to a method ofleast squares.

A first image processing method of the present invention includes: arelational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of image data, mixed pixeldata, which is pixel data, in which a plurality of objects contained inthe image data are mixed, from the designated frame and a peripheralframe around the designated frame in accordance with a motion of aforeground object which forms a foreground of the plurality of objects,and also of extracting, in correspondence with the mixed pixel data,background pixel data, which is the pixel data, corresponding to abackground object which forms a background of the plurality of objects,the background pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject, so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and a mixture-ratiodetection step of detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions. In the relational-expressiongenerating step, the plurality of relational expressions are generatedbased on a first approximation in which components of the foregroundobject contained in the mixed pixel data change substantially linearlywith respect to the positions of the pixels, and a second approximationin which the mixture ratio of the mixed pixel data extracted from thedesignated frame changes substantially linear with respect to thepositions of the pixels.

The image processing method may further include a foreground/backgroundseparation step of separating the image data into a foreground objectimage consisting of only the foreground object components which form theforeground object in the image data and a background object imageconsisting of only background object components which form thebackground object in the image data based on the mixture ratiocorresponding to the designated pixel.

In the mixture-ratio detection step, the mixture ratio may be detectedby solving the plurality of relational expressions according to a methodof least squares.

A program of a first recording medium of the present invention includes:a relational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of image data, mixed pixeldata, which is pixel data, in which a plurality of objects contained inthe image data are mixed, from the designated frame and a peripheralframe around the designated frame in accordance with a motion of aforeground object which forms a foreground of the plurality of objects,and also of extracting, in correspondence with the mixed pixel data,background pixel data, which is the pixel data, corresponding to abackground object which forms a background of the plurality of objects,the background pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject, so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and a mixture-ratiodetection step of detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions. In the relational-expressiongenerating step, the plurality of relational expressions are generatedbased on a first approximation in which components of the foregroundobject contained in the mixed pixel data change substantially linearlywith respect to the positions of the pixels, and a second approximationin which the mixture ratio of the mixed pixel data extracted from thedesignated frame changes. substantially linear with respect to thepositions of the pixels.

The program may further include a foreground/background separation stepof separating the image data into a foreground object image consistingof only the foreground object components which form the foregroundobject in the image data and a background object image consisting ofonly background object components which form the background object inthe image data based on the mixture ratio corresponding to thedesignated pixel.

In the mixture-ratio detection step, the mixture ratio may be detectedby solving the plurality of relational expressions according to a methodof least squares.

A first program of the present invention allows a computer to execute: arelational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of image data, mixed pixeldata, which is pixel data, in which a plurality of objects contained inthe image data are mixed, from the designated frame and a peripheralframe around the designated frame in accordance with a motion of aforeground object which forms a foreground of the plurality of objects,and also of extracting, in correspondence with the mixed pixel data,background pixel data, which is the pixel data, corresponding to abackground object which forms a background of the plurality of objects,the background pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and a mixture-ratiodetection step of detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions. In the relational-expressiongenerating step, the plurality of relational expressions are generatedbased on a first approximation in which components of the foregroundobject contained in the mixed pixel data change substantially linearlywith respect to the positions of the pixels, and a second approximationin which the mixture ratio of the mixed pixel data extracted from thedesignated frame changes substantially linear with respect to thepositions of the pixels.

The program may further include a foreground/background separation stepof separating the image data into a foreground object image consistingof only the foreground object components which form the foregroundobject in the image data and a background object image consisting ofonly background object components which form the background object inthe image data based on the mixture ratio corresponding to thedesignated pixel.

In the mixture-ratio detection step, the mixture ratio may be detectedby solving the plurality of relational expressions according to a methodof least squares.

A first image-capturing apparatus of the present invention includes:image-capturing means for outputting a subject image captured by animage-capturing device including a predetermined number of pixels havinga time integrating function as image data consisting of a predeterminednumber of pixel data; relational-expression generating means forextracting, in correspondence with a designated pixel of a designatedframe of the image data, mixed pixel data, which is the pixel data, inwhich a plurality of objects contained in the image data are mixed, fromthe designated frame and a peripheral frame around the designated framein accordance with a motion of a foreground object which forms aforeground of the plurality of objects, and also for extracting, incorrespondence with the mixed pixel data, background pixel data, whichis the pixel data, corresponding to a background object which forms abackground of the plurality of objects, the background pixel data beingassociated with the corresponding mixed pixel data, from a framedifferent from the frames from which the mixed pixel data are extractedin accordance with a motion of the background object so as to generate aplurality of relational expressions indicating relationships between themixed pixel data and the background pixel data concerning the designatedpixel; and mixture-ratio detection means for detecting a mixture ratioindicating a mixture state of the plurality of objects in the real worldconcerning the designated pixel based on the relational expressions. Therelational-expression generating means generates the plurality ofrelational expressions based on a first approximation in whichcomponents of the foreground object contained in the mixed pixel datachange substantially linearly with respect to the positions of thepixels, and a second approximation in which the mixture ratio of themixed pixel data extracted from the designated frame changessubstantially linearly with respect to the positions of the pixels.

The image-capturing apparatus may further include foreground/backgroundseparation means for separating the image data into a foreground objectimage consisting of only the foreground object components which form theforeground object in the image data and a background object imageconsisting of only background object components which form thebackground object in the image data based on the mixture ratiocorresponding to the designated pixel.

The mixture-ratio detection means may detect the mixture ratio bysolving the plurality of relational expressions according to a method ofleast squares.

A second image processing apparatus of the present invention includes:relational-expression generating means for extracting, in correspondencewith a designated pixel of a designated frame of image data, pixel dataof a peripheral frame around the designated frame as background pixeldata corresponding to a background object of a plurality of objects ofthe image data, and also for extracting designated pixel data of thedesignated pixel and proximity pixel data of a pixel located in closeproximity with the designated pixel in the designated frame so as togenerate a plurality of relational expressions indicating relationshipsof the designated pixel data, the proximity pixel data, and thebackground pixel data corresponding to the designated pixel data or theproximity pixel data concerning the designated pixel; and mixture-ratiodetection means for detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions. The relational-expressiongenerating means generates the plurality of relational expressions basedon an approximation in which the mixture ratio corresponding to thedesignated pixel and the proximity pixel is uniform.

The relational-expression generating means may generate the plurality ofrelational expressions based on an approximation in which components ofa foreground object of the plurality of objects contained in thedesignated pixel data and the proximity pixel data are uniform.

The relational-expression generating means may generate the plurality ofrelational expressions based on an approximation in which components ofa foreground object of the plurality of objects contained in thedesignated pixel data and the proximity pixel data change substantiallylinearly with respect to the positions of the pixels.

The image processing apparatus may include foreground/backgroundseparation means for separating the image data into a foreground objectimage consisting of only the foreground object components which form theforeground object in the image data and a background object imageconsisting of only background object components which form thebackground object in the image data based on the mixture ratiocorresponding to the designated pixel.

The mixture-ratio detection means may detect the mixture ratio bysolving the plurality of relational expressions according to a method ofleast squares.

A second image processing method of the present invention includes: arelational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of the image data, pixeldata of a peripheral frame around the designated frame as backgroundpixel data corresponding to a background object of a plurality ofobjects of the image data, and also of extracting designated pixel dataof the designated pixel and proximity pixel data of a pixel located inclose proximity with the designated pixel in the designated frame so asto generate a plurality of relational expressions indicatingrelationships of the designated pixel data, the proximity pixel data,and the background pixel data corresponding to the designated pixel dataor the proximity pixel data concerning the designated pixel; and amixture-ratio detection step of detecting a mixture ratio indicating amixture state of the plurality of objects in the real world concerningthe designated pixel based on the relational expressions. In therelational-expression generating step, the plurality of relationalexpressions are generated based on an approximation in which the mixtureratio corresponding to the designated pixel and the proximity pixel isuniform.

In the relational-expression generating step, the plurality ofrelational expressions may be generated based on an approximation inwhich components of a foreground object of the plurality of objectscontained in the designated pixel data and the proximity pixel data areuniform.

In the relational-expression generating step, the plurality ofrelational expressions may be generated based on an approximation inwhich components of a foreground object of the plurality of objectscontained in the designated pixel data and the proximity pixel datachange substantially linearly with respect to the positions of thepixels.

The image processing method may further include a foreground/backgroundseparation step of separating the image data into a foreground objectimage consisting of only the foreground object components which form theforeground object in the image data and a background object imageconsisting of only background object components which form thebackground object in the image data based on the mixture ratiocorresponding to the designated pixel.

In the mixture-ratio detection step, the mixture ratio may be detectedby solving the plurality of relational expressions according to a methodof least squares.

A program of a second recording medium of the present inventionincludes: a relational-expression generating step of extracting, incorrespondence with a designated pixel of a designated frame of imagedata, pixel data of a peripheral frame around the designated frame asbackground pixel data corresponding to a background object of aplurality of objects of the image data, and also of extractingdesignated pixel data of the designated pixel and proximity pixel dataof a pixel located in close proximity with the designated pixel in thedesignated frame so as to generate a plurality of relational expressionsindicating relationships of the designated pixel data, the proximitypixel data, and the background pixel data corresponding to thedesignated pixel data or the proximity pixel data concerning thedesignated pixel; and a mixture-ratio detection step of detecting amixture ratio indicating a mixture state of the plurality of objects inthe real world concerning the designated pixel based on the relationalexpressions. In the relational-expression generating-step, the pluralityof relational expressions are generated based on an approximation inwhich the mixture ratio corresponding to the designated pixel and theproximity pixel is uniform.

In the relational-expression generating step, the plurality ofrelational expressions may be generated based on an approximation inwhich components of a foreground object of the plurality of objectscontained in the designated pixel data and the proximity pixel data areuniform.

In the relational-expression generating step, the plurality ofrelational expressions may be generated based on an approximation inwhich components of a foreground object of the plurality of objectscontained in the designated pixel data and the proximity pixel datachange substantially linearly with respect to the positions of thepixels.

The program may include a foreground/background separation step ofseparating the image data into a foreground object image consisting ofonly the foreground object components which form the foreground objectin the image data and a background object image consisting of onlybackground object components which form the background object in theimage data based on the mixture ratio corresponding to the designatedpixel.

In the mixture-ratio detection step, the mixture ratio may be detectedby solving the plurality of relational expressions according to a methodof least squares.

A second program of the present invention allows a computer to execute:a relational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of image data, pixel dataof a peripheral frame around the designated frame as background pixeldata corresponding to a background object of a plurality of objects ofthe image data, and also of extracting designated pixel data of thedesignated pixel and proximity pixel data of a pixel located in closeproximity with the designated pixel in the designated frame so as togenerate a plurality of relational expressions indicating relationshipsof the designated pixel data, the proximity pixel data, and thebackground pixel data corresponding to the designated pixel data or theproximity pixel data concerning the designated pixel; and amixture-ratio detection step of detecting a mixture ratio indicating amixture state of the plurality of objects in the real world concerningthe designated pixel based on the relational expressions. In therelational-expression generating step, the plurality of relationalexpressions are generated based on an approximation in which the mixtureratio corresponding to the designated pixel and the proximity pixel isuniform.

In the relational-expression generating step, the plurality ofrelational expressions may be generated based on an approximation inwhich components of a foreground object of the plurality of objectscontained in the designated pixel data and the proximity pixel data areuniform.

In the relational-expression generating step, the plurality ofrelational expressions may be generated based on an approximation inwhich components of a foreground object of the plurality of objectscontained in the designated pixel data and the proximity pixel datachange substantially linearly with respect to the positions of thepixels.

The program may further include a foreground/background separation stepof separating the image data into a foreground object image consistingof only the foreground object components which form the foregroundobject in the image data and a background object image consisting ofonly background object components which form the background object inthe image data based on the mixture ratio corresponding to thedesignated pixel.

In the mixture-ratio detection step, the mixture ratio may be detectedby solving the plurality of relational expressions according to a methodof least squares.

A second image-capturing apparatus of the present invention includes:image-capturing means for outputting a subject image captured by animage-capturing device including a predetermined number of pixels havinga time integrating function as image data consisting of a predeterminednumber of pixel data; relational-expression generating means forextracting, in correspondence with a designated pixel of a designatedframe of the image data, pixel data of a peripheral frame around thedesignated frame as background pixel data corresponding to a backgroundobject of a plurality of objects of the image data, and also forextracting designated pixel data of the designated pixel and proximitypixel data of a pixel located in close proximity with the designatedpixel in the designated frame so as to generate a plurality ofrelational expressions indicating relationships of the designated pixeldata, the proximity pixel data, and the background pixel datacorresponding to the designated pixel data or the proximity pixel dataconcerning the designated pixel; and mixture-ratio detection means fordetecting a mixture ratio indicating a mixture state of the plurality ofobjects in the real world concerning the designated pixel based on therelational expressions. The relational-expression generating meansgenerates the plurality of relational expressions based on anapproximation in which the mixture ratio corresponding to the designatedpixel and the proximity pixel is uniform.

The relational-expression generating means may generate the plurality ofrelational expressions based on an approximation in which components ofa foreground object of the plurality of objects contained in thedesignated pixel data and the proximity pixel data are uniform.

The relational-expression generating means may generate the plurality ofrelational expressions based on an approximation in which components ofa foreground object of the plurality of objects contained in thedesignated pixel data and the proximity pixel data change substantiallylinearly with respect to the positions of the pixels.

The image-capturing apparatus may further include foreground/backgroundseparation means for separating the image data into a foreground objectimage consisting of only the foreground object components which form theforeground object in the image data and a background object imageconsisting of only background object components which form thebackground object in the image data based on the mixture ratiocorresponding to the designated pixel.

The mixture-ratio detection means may detect the mixture ratio bysolving the plurality of relational expressions according to a method ofleast squares.

In correspondence with a designated pixel of a designated frame of imagedata, mixed pixel data, which is pixel data, in which a plurality ofobjects contained in the image data are mixed, are extracted from thedesignated frame and a peripheral frame around the designated frame inaccordance with a motion of a foreground object which forms a foregroundof the plurality of objects. Also, in correspondence with the mixedpixel data, background pixel data, which is the pixel data,corresponding to a background object which forms a background of theplurality of objects, the background pixel data being associated withthe corresponding mixed pixel data, are extracted from a frame differentfrom the frames from which the mixed pixel data are extracted inaccordance with a motion of the background object. A plurality ofrelational expressions indicating relationships between the mixed pixeldata and the background pixel data are generated concerning thedesignated pixel. A mixture ratio indicating a mixture state of theplurality of objects in the real world is detected concerning thedesignated pixel based on the relational expressions. In the generationof the relational expressions, the plurality of relational expressionsare generated based on a first approximation in which components of theforeground object contained in the mixed pixel data change substantiallylinearly with respect to the positions of the pixels, and a secondapproximation in which the mixture ratio of the mixed pixel dataextracted from the designated frame changes substantially linearly withrespect to the positions of the pixels.

In correspondence with a designated pixel of a designated frame of theimage data, pixel data of a peripheral frame around the designated frameare extracted as background pixel data corresponding to a backgroundobject of a plurality of objects of the image data. Also, designatedpixel data of the designated pixel and proximity pixel data of a pixellocated in close proximity with the designated pixel in the designatedframe are extracted. A plurality of relational expressions indicatingrelationships of the designated pixel data, the proximity pixel data,and the background pixel data corresponding to the designated pixel dataor the proximity pixel data are generated concerning the designatedpixel. A mixture ratio indicating a mixture state of the plurality ofobjects in the real world is detected concerning the designated pixelbased on the relational expressions. In the generation of the relationalexpression, the plurality of relational expressions are generated basedon an approximation in which the mixture ratio corresponding to thedesignated pixel and the proximity pixel is uniform.

With this arrangement, the mixture ratio indicating the mixture state ofa plurality of objects, such as a background image and a moving objectimage, can be detected.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates the principle of the present invention.

FIG. 2 is a block diagram illustrating an example of the configurationto which the present invention is applied.

FIG. 3 is a block diagram illustrating an example of the configurationof a signal processor 12 shown in FIG. 2.

FIG. 4 is a block diagram illustrating the signal processor 12.

FIG. 5 illustrates the image capturing performed by a sensor.

FIG. 6 illustrates the arrangement of pixels.

FIG. 7 illustrates the operation of a detection device.

FIG. 8A illustrates an image obtained by image-capturing an objectcorresponding to a moving foreground and an object corresponding to astationary background.

FIG. 8B illustrates a model of an image obtained by image-capturing anobject corresponding to a moving foreground and an object correspondingto a stationary background.

FIG. 9 illustrates a background area, a foreground area, a mixed area, acovered background area, and an uncovered background area.

FIG. 10 illustrates a model obtained by expanding in the time directionthe pixel values of pixels aligned side-by-side in an image obtained byimage-capturing an object corresponding to a stationary foreground andan the object corresponding to a stationary background.

FIG. 11 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 12 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 13 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 14 illustrates an example in which pixels in a foreground area, abackground area, and a mixed area are extracted.

FIG. 15 illustrates the relationships between pixels and a modelobtained by expanding the pixel values in the time direction.

FIG. 16 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 17 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 18 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 19 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 20 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 21 is a flowchart illustrating the processing for adjusting theamount of motion blur.

FIG. 22 is a block diagram illustrating an example of the configurationof an area specifying unit 103.

FIG. 23 illustrates an image when an object corresponding to aforeground is moving.

FIG. 24 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 25 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 26 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 27 illustrates the conditions for determining the area.

FIG. 28A illustrates an example of the result obtained by specifying thearea by the area specifying unit 103.

FIG. 28B illustrates an example of the result obtained by specifying thearea by the area specifying unit 103.

FIG. 28C illustrates an example of the result obtained by specifying thearea by the area specifying unit 103.

FIG. 28D illustrates an example of the result obtained by specifying thearea by the area specifying unit 103.

FIG. 29 illustrates an example of the result obtained by specifying thearea by the area specifying unit 103.

FIG. 30 is a flowchart illustrating the area specifying processing.

FIG. 31 is a block diagram illustrating another configuration of thearea specifying unit 103.

FIG. 32 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 33 illustrates an example of a background image.

FIG. 34 is a block diagram illustrating the configuration of abinary-object-image extracting portion 302.

FIG. 35A illustrates the calculation of a correlation value.

FIG. 35B illustrates the calculation of a correlation value.

FIG. 36A illustrates the calculation of a correlation value.

FIG. 36B illustrates the calculation of a correlation value.

FIG. 37 illustrates an example of the binary object image.

FIG. 38 is a block diagram illustrating the configuration of a timechange detector 303.

FIG. 39 illustrates determinations made by an area determining portion342.

FIG. 40 illustrates an example of determinations made by the time changedetector 303.

FIG. 41 is a flowchart illustrating the area specifying processingperformed by the area specifying unit 103.

FIG. 42 is a flowchart illustrating details of the area specifyingprocessing.

FIG. 43 is a block diagram illustrating still another configuration ofthe area specifying unit 103.

FIG. 44 is a block diagram illustrating the configuration of arobust-processing portion 361.

FIG. 45 illustrates motion compensation performed by a motioncompensator 381.

FIG. 46 illustrates motion compensation performed by the motioncompensator 381.

FIG. 47 is a flowchart illustrating the area specifying processing.

FIG. 48 is a flowchart illustrating details of the robust processing.

FIG. 49 is a block diagram illustrating the configuration of amixture-ratio calculator 104.

FIG. 50 illustrates an example of the ideal mixture ratio a.

FIG. 51 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 52 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 53 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 54 illustrates a straight line for approximating the mixture ratioα.

FIG. 55 illustrates a plane for approximating the mixture ratio α.

FIG. 56 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided FIG. 57 illustrates the relationships of the pixels in aplurality of frames when the mixture ratio α is calculated.

FIG. 58 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 59 is a block diagram illustrating the configuration of themixture-ratio estimation processor 401.

FIG. 60 is a block diagram illustrating another configuration of themixture-ratio calculator 104.

FIG. 61 is a flowchart illustrating the processing for calculating themixture ratio.

FIG. 62 is a flowchart illustrating the processing for calculating theestimated mixture ratio.

FIG. 63 is a block diagram illustrating the configuration of themixture-ratio calculator 104.

FIG. 64 illustrates a straight line for approximating the mixture ratioα.

FIG. 65 illustrates a plane for approximating the mixture ratio α.

FIG. 66 illustrates the relationships of the pixels in a plurality offrames when the mixture ratio α is calculated.

FIG. 67 illustrates the relationships of the pixels in a plurality offrames when the mixture ratio α is calculated.

FIG. 68 is a block diagram illustrating the configuration of theestimated mixture-ratio processor 501.

FIG. 69 is a block diagram illustrating the configuration of amixture-ratio calculator 522.

FIG. 70 is a flowchart illustrating the mixture-ratio calculationprocessing.

FIG. 71 is a flowchart illustrating the mixture-ratio estimatingprocessing by using a model corresponding to a covered background area.

FIG. 72 is a block diagram illustrating an example of the configurationof a foreground/background separator 105.

FIG. 73A illustrates an input image, a foreground component image, and abackground component image.

FIG. 73B illustrates a model of an input image, a foreground componentimage, and a background component image.

FIG. 74 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 75 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 76 illustrates a model in which pixel values are expanded in thetime direction and the period corresponding to the shutter time isdivided.

FIG. 77 is a block diagram illustrating an example of the configurationof a separating portion 601.

FIG. 78A illustrates an example of a separated foreground componentimage.

FIG. 78B illustrates an example of a separated background componentimage.

FIG. 79 is a flowchart illustrating the processing for separating aforeground and a background.

FIG. 80 is a block diagram illustrating an example of the configurationof a motion-blur adjusting unit 106.

FIG. 81 illustrates the unit of processing.

FIG. 82 illustrates a model in which the pixel values of a foregroundcomponent image are expanded in the time direction and the periodcorresponding to the shutter time is divided.

FIG. 83 illustrates a model in which the pixel values of a foregroundcomponent image are expanded in the time direction and the periodcorresponding to the shutter time is divided.

FIG. 84 illustrates a model in which the pixel values of a foregroundcomponent image are expanded in the time direction and the periodcorresponding to the shutter time is divided.

FIG. 85 illustrates a model in which the pixel values of a foregroundcomponent image are expanded in the time direction and the periodcorresponding to the shutter time is divided.

FIG. 86 illustrates an example of another configuration of themotion-blur adjusting unit 106.

FIG. 87 is a flowchart illustrating the processing for adjusting theamount of motion blur contained in a foreground component imageperformed by the motion-blur adjusting unit 106.

FIG. 88 is a block diagram illustrating an example of anotherconfiguration of the motion-blur adjusting unit 106.

FIG. 89 illustrates an example of a model in which the relationshipsbetween pixel values and foreground components are indicated.

FIG. 90 illustrates the calculation of foreground components.

FIG. 91 illustrates the calculation of foreground components.

FIG. 92 is a flowchart illustrating the processing for eliminatingmotion blur contained in a foreground.

FIG. 93 is a block diagram illustrating another configuration of thefunction of the signal processor 12.

FIG. 94 illustrates the configuration of a synthesizer 1001.

FIG. 95 is a block diagram illustrating another configuration of thefunction of the signal processor 12.

FIG. 96 is a block diagram illustrating still another configuration ofthe function of the signal processor 12.

FIG. 97 is a block diagram illustrating the configuration of amixture-ratio calculator 1101.

FIG. 98 is a block diagram illustrating the configuration of aforeground/background separator 1102.

FIG. 99 is a block diagram illustrating still another configuration ofthe function of the signal processor 12.

FIG. 100 is a block diagram illustrating the configuration of amixture-ratio calculator 1101.

FIG. 101 is a block diagram illustrating still another configuration ofthe function of the signal processor 12.

FIG. 102 illustrates the configuration of a synthesizer 1201.

FIG. 103 is a block diagram illustrating still another configuration ofthe function of the signal processor 12.

BEST MODE FOR CARRYING OUT THE INVENTION

FIG. 1 illustrates the principle of the present invention. As shown inFIG. 1, a first signal, which is information of a real society 1 havinga space and a time axis, is obtained by a sensor 2, and is formed intodata. Data 3, which is the detection signal obtained by the sensor 2, isinformation obtained by projecting the information of the real society 1onto a time space having a dimension lower than the real society.Accordingly, the projected information has distortion caused by theprojection. In other words, the data 3 output from the sensor 2 hasdistortion with respect to the information of the real society 1.Although the data 3 has distortion caused by the projection, it containssignificant information for correcting for the distortion.

Accordingly, in the present invention, by performing signal processingon the data output from the sensor 2 by a signal processor 4,significant information can be extracted.

By using this significant information, the distortion can be removed,reduced, or adjusted.

FIG. 2 illustrates an example of the configuration of a signalprocessing apparatus to which the present invention is applied. A sensor11, which is formed of, for example, a video camera, captures an imageof the real society, and outputs the obtained image data to a signalprocessor 12. The signal processor 12, which is formed of, for example,a personal computer, processes the data input from the sensor 11,adjusts the amount of distortion caused by the projection, specifies thearea in which significant information is embedded by the projection,extracts the significant information from the specified area, orprocesses the input data based on the extracted significant information.

The above-described significant information is, for example, the mixtureratio, which is discussed below.

It can be considered that the information indicating the area in whichthe significant information embedded by the projection is contained isalso significant information. The area information, which is describedbelow, corresponds to the significant information.

The area in which the significant information is contained is, forexample, a mixed area, which is discussed below.

The signal processor 12 is configured, for example, as shown in FIG. 3.A CPU (Central Processing Unit) 21 executes various types of processingaccording to programs stored in a ROM (Read Only Memory) 22 or in astorage unit 28. Programs executed by the CPU 21 and data are stored ina RAM (Random Access Memory) 23 as required. The CPU 21, the ROM 22, andthe RAM 23 are connected to each other by a bus 24.

An input/output interface 25 is also connected to the CPU 21 via the bus24. An input unit 26, which is formed of a keyboard, a mouse, amicrophone, and so on, and an output unit 27, which is formed of adisplay, a speaker, and so on, are connected to the input/outputinterface 25. The CPU 21 executes various types of processing inresponse to a command input from the input unit 26. The CPU 21 thenoutputs an image or sound obtained as a result of the processing to theoutput unit 27.

The storage unit 28 connected to the input/output interface 25 is formedof, for example, a hard disk, and stores programs executed by the CPU 21and various types of data. A communication unit 29 communicates with anexternal device via the Internet or another network. In this example,the communication unit 29 serves as an obtaining unit for obtaining anoutput of a sensor.

Alternatively, a program may be obtained via the communication unit 29and stored in the storage unit 28.

A drive 30 connected to the input/output interface 25 drives a magneticdisk 51, an optical disc 52, a magneto-optical disk 53, a semiconductormemory 54, or the like, when such a recording medium is attached to thedrive 30, and obtains a program or data stored in the correspondingmedium. The obtained program or data is transferred to the storage unit28 and stored therein if necessary.

By taking a more specific example, a description is now given of asignal processing apparatus which performs processing, such asspecifying an area having significant information embedded therein orextracting significant information embedded therein from data obtainedby a sensor. In the subsequent example, a CCD line sensor or a CCD areasensor corresponds to the sensor, the area information or the mixtureratio corresponds to the significant information, and the mixture stateof a foreground and a background or motion blur in a mixed areacorresponds to distortion.

FIG. 4 is a block diagram illustrating the signal processor 12.

It does not matter whether the individual functions of the signalprocessor 12 are implemented by hardware or software. That is, the blockdiagrams of this specification may be hardware block diagrams orsoftware functional block diagrams.

Motion blur is a distortion contained in an image corresponding to amoving object caused by the movement of an object to be captured in thereal world and the image-capturing characteristics of the sensor 11.

In this specification, an image to be captured corresponding to anobject in the real world is referred to as an image object.

An input image supplied to the signal processor 12 is supplied to anobject extracting unit 101, an area specifying unit 103, a mixture-ratiocalculator 104, and a foreground/background separator 105.

The object extracting unit 101 extracts a rough image objectcorresponding to a foreground object contained in the input image, andsupplies the extracted image object to a motion detector 102. The objectextracting unit 101 detects, for example, an outline of the foregroundimage object contained in the input image so as to extract a rough imageobject corresponding to the foreground object.

The object extracting unit 101 extracts a rough image objectcorresponding to a background object contained in the input image, andsupplies the extracted image object to the motion detector 102. Theobject extracting unit 101 extracts a rough image object correspondingto the background object from, for example, the difference between theinput image and the extracted image object corresponding to theforeground object.

Alternatively, for example, the object extracting unit 101 may extractthe rough image object corresponding to the foreground object and therough image object corresponding to the background object from thedifference between the background image stored in a built-in backgroundmemory and the input image.

The motion detector 102 calculates a motion vector of the roughlyextracted image object corresponding to the foreground object accordingto a technique, such as block matching, gradient, phase correlation, orpel-recursive technique, and supplies the calculated motion vector andthe motion-vector positional information (which is information forspecifying the positions of the pixels corresponding to the motionvector) to the area specifying unit 103, the mixture-ratio calculator104, and a motion-blur extracting unit 106.

The motion vector output from the motion detector 102 containsinformation corresponding to the amount of movement v.

The motion detector 102 may output the motion vector of each imageobject, together with the pixel positional information for specifyingthe pixels of the image object, to the motion-blur adjusting unit 106.

The amount of movement v is a value indicating a positional change in animage corresponding to a moving object in units of the pixel pitch. Forexample, if an object image corresponding to a foreground is moving suchthat it is displayed at a position four pixels away from a referenceframe when it is positioned in the subsequent frame, the amount ofmovement v of the object image corresponding to the foreground is 4.

The object extracting unit 101 and the motion detector 102 are neededwhen adjusting the amount of motion blur corresponding to a movingobject.

The area specifying unit 103 determines to which of a foreground area, abackground area, or a mixed area each pixel of the input image belongs,and supplies information indicating to which area each pixel belongs(hereinafter referred to as “area information”) to the mixture-ratiocalculator 104, the foreground/background separator 105, and themotion-blur adjusting unit 106.

The mixture-ratio calculator 104 calculates the mixture ratiocorresponding to the pixels contained in a mixed area 63 (hereinafterreferred to as the “mixture ratio α”) based on the input image, themotion vector and the positional information thereof supplied from themotion detector 102, and the area information supplied from the areaspecifying unit 103, and supplies the mixture ratio α to theforeground/background separator 105.

The mixture ratio ax is a value indicating the ratio of the imagecomponents corresponding to the background object (hereinafter also bereferred to as “background components”) to the pixel value as expressedby equation (3), which is shown below.

The foreground/background separator 105 separates the input image into aforeground component image formed of only the image componentscorresponding to the foreground object (hereinafter also be referred toas “foreground components”) and a background component image formed ofonly the background components based on the area information suppliedfrom the area specifying unit 103 and the mixture ratio a supplied fromthe mixture-ratio calculator 104, and supplies the foreground componentimage to the motion-blur adjusting unit 106 and a selector 107. Theseparated foreground component image may be set as the final output. Amore precise foreground and background can be obtained compared to aknown method in which only a foreground and a background are specifiedwithout considering the mixed area.

The motion-blur adjusting unit 106 determines the unit of processingindicating at least one pixel contained in the foreground componentimage based on the amount of movement v obtained from the motion vectorand based on the area information. The unit of processing is data thatspecifies a group of pixels to be subjected to the motion-bluradjustments.

Based on the amount by which the motion blur is to be adjusted, which isinput into the signal processor 12, the foreground component imagesupplied from the foreground/background separator 105, the motion vectorand the positional information thereof supplied from the motion detector102, and the unit of processing, the motion-blur adjusting unit 106adjusts the amount of motion blur contained in the foreground componentimage by removing, decreasing, or increasing the motion blur containedin the foreground component image. The motion-blur adjusting unit 106then outputs the foreground component image in which amount of motionblur is adjusted to the selector 107. It is not essential that themotion vector and the positional information thereof be used.

The selector 107 selects one of the foreground component image suppliedfrom the foreground/background separator 105 and the foregroundcomponent image in which the amount of motion blur is adjusted suppliedfrom the motion-blur adjusting unit 106 based on, for example, aselection signal reflecting a user's selection, and outputs the selectedforeground component image.

An input image supplied to the signal processor 12 is discussed belowwith reference to FIGS. 5 through 20.

FIG. 5 illustrates image capturing performed by a sensor. The sensor 11is formed of, for example; a CCD (Charge-Coupled Device) video cameraprovided with a CCD area sensor, which is a solid-state image-capturingdevice. An object 111 corresponding to a foreground in the real worldmoves, for example, horizontally from the left to the right, between anobject 112 corresponding to a background and the sensor.

The sensor 11 captures the image of the object 111 corresponding to theforeground together with the image of the object 112 corresponding tothe background. The sensor 11 outputs the captured image in units offrames. For example, the sensor 11 outputs an image having 30 frames persecond. The exposure time of the sensor 11 can be 1/30 second. Theexposure time is a period from when the sensor 11 starts convertinginput light into electrical charge until when the conversion from theinput light to the electrical charge is finished. The exposure time isalso referred to as a “shutter time”.

FIG. 6 illustrates the arrangement of pixels. In FIG. 6, A through Iindicate the individual pixels. The pixels are disposed on a plane of acorresponding image. One detection device corresponding to each pixel isdisposed on the sensor 11. When the sensor 11 performs image capturing,each detection device outputs a pixel value of the corresponding pixelforming the image. For example, the position of the detection device inthe X direction corresponds to the horizontal direction on the image,while the position of the detection device in the Y directioncorresponds to the vertical direction on the image.

As shown in FIG. 7, the detection device, which is, for example, a CCD,converts input light into electrical charge during a periodcorresponding to a shutter time, and stores the converted electricalcharge. The amount of charge is almost proportional to the intensity ofthe input light and the period for which the light is input. Thedetection device sequentially adds the electrical charge converted fromthe input light to the stored electrical charge during the periodcorresponding to the shutter time. That is, the detection deviceintegrates the input light during the period corresponding to theshutter time and stores the electrical charge corresponding to theamount of integrated light. It can be considered that the detectiondevice has an integrating function with respect to time.

The electrical charge stored in the detection device is converted into avoltage value by a circuit (not shown), and the voltage value is furtherconverted into a pixel value, such as digital data, and is output.Accordingly, each pixel value output from the sensor 11 is a valueprojected on a linear space, which is a result of integrating a certainthree-dimensional portion of the object corresponding to the foregroundor the background with respect to the shutter time.

The signal processor 12 extracts significant information embedded in theoutput signal, for example, the mixture ratio α, by the storageoperation of the sensor 11. The signal processor 12 adjusts the amountof distortion, for example, the amount of motion blur, caused by themixture of the foreground image object itself. The signal processor 12also adjusts the amount of distortion caused by the mixture of theforeground image object and the background image object.

FIG. 8A illustrates an image obtained by capturing a moving objectcorresponding to a foreground and a stationary object corresponding to abackground. In the example shown in FIG. 8A, the object corresponding tothe foreground is moving horizontally from the left to the right withrespect to the screen.

FIG. 8B illustrates a model obtained by expanding pixel valuescorresponding to one line of the image shown in FIG. 8A in the timedirection. The horizontal direction shown in FIG. 8B corresponds to thespatial direction X in FIG. 8A.

The values of the pixels in the background area are formed only from thebackground components, that is, the image components corresponding tothe background object. The values of the pixels in the foreground areaare formed only from the foreground components, that is, the imagecomponents corresponding to the foreground object.

The values of the pixels of the mixed area are formed from thebackground components and the foreground components. Since the values ofthe pixels in the mixed area are formed from the background componentsand the foreground components, it may be referred to as a “distortionarea”. The mixed area is further classified into a covered backgroundarea and an uncovered background area.

The covered background area is a mixed area at a position correspondingto the leading end in the direction in which the foreground object ismoving, where the background components are gradually covered with theforeground over time.

In contrast, the uncovered background area is a mixed area correspondingto the trailing end in the direction in which the foreground object ismoving, where the background components gradually appear over time.

As discussed above, the image containing the foreground area, thebackground area, or the covered background area or the uncoveredbackground area is input into the area specifying unit 103, themixture-ratio calculator 104, and the foreground/background separator105 as the input image.

FIG. 9 illustrates the background area, the foreground area, the mixedarea, the covered background area, and the uncovered background areadiscussed above. In the areas corresponding to the image shown in FIG.8A, the background area is a stationary portion, the foreground area isa moving portion, the covered background area of the mixed area is aportion that changes from the background to the foreground, and theuncovered background area of the mixed area is a portion that changesfrom the foreground to the background.

FIG. 10 illustrates a model obtained by expanding in the time directionthe pixel values of the pixels aligned side-by-side in the imageobtained by capturing the image of the object corresponding to thestationary foreground and the image of the object corresponding to thestationary background. For example, as the pixels aligned side-by-side,pixels arranged in one line on the screen can be selected.

The pixel values indicated by F01 through F04 shown in FIG. 10 arevalues of the pixels corresponding to the object of the stationaryforeground. The pixel values indicated by B01 through B04 shown in FIG.10 are values of the pixels corresponding to the object of thestationary background.

Time elapses from the top to the bottom in FIG. 10 in the verticaldirection in FIG. 10. The position at the top side of the rectangle inFIG. 10 corresponds to the time at which the sensor 11 starts convertinginput light into electrical charge, and the position at the bottom sideof the rectangle in FIG. 10 corresponds to the time at which theconversion from the input light into the electrical charge is finished.That is, the distance from the top side to the bottom side of therectangle in FIG. 10 corresponds to the shutter time.

The pixels shown in FIG. 10 are described below assuming that, forexample, the shutter time is equal to the frame size.

The horizontal direction in FIG. 10 corresponds to the spatial directionX in FIG. 8A. More specifically, in the example shown in FIG. 10, thedistance from the left side of the rectangle indicated by “F01” in FIG.10 to the right side of the rectangle indicated by “B04” is eight timesthe pixel pitch, i.e., eight consecutive pixels.

When the foreground object and the background object are stationary, thelight input into the sensor 11 does not change during the periodcorresponding to the shutter time.

The period corresponding to the shutter time is divided into two or moreportions of equal periods. For example, if the number of virtual dividedportions is 4, the model shown in FIG. 10 can be represented by themodel shown in FIG. 11. The number of virtual divided portions can beset according to the amount of movement v of the object corresponding tothe foreground within the shutter time. For example, the number ofvirtual divided portions is set to 4 when the amount of movement v is 4,and the period corresponding to the shutter time is divided into fourportions.

The uppermost line in FIG. 11 corresponds to the first divided periodfrom when the shutter has opened. The second line in FIG. 11 correspondsto the second divided period from when the shutter has opened. The thirdline in FIG. 11 corresponds to the third divided period from when theshutter has opened. The fourth line in FIG. 11 corresponds to the fourthdivided period from when the shutter has opened.

The shutter time divided in accordance with the amount of movement v isalso hereinafter referred to as the “shutter time/v”.

When the object corresponding to the foreground is stationary, the lightinput into the sensor 11 does not change, and thus, the foregroundcomponent F01/v is equal to the value obtained by dividing the pixelvalue F01 by the number of virtual divided portions. Similarly, when theobject corresponding to the foreground is stationary, the foregroundcomponent F02/v is equal to the value obtained by dividing the pixelvalue F02 by the number of virtual divided portions, the foregroundcomponent F03/v is equal to the value obtained by dividing the pixelvalue F03 by the number of virtual divided portions, and the foregroundcomponent F04/v is equal to the value obtained by dividing the pixelvalue F04 by the number of virtual divided portions.

When the object corresponding to the background is stationary, the lightinput into the sensor 11 does not change, and thus, the backgroundcomponent B01/v is equal to the value obtained by dividing the pixelvalue B01 by the number of virtual divided portions. Similarly, when theobject corresponding to the background is stationary, the backgroundcomponent B02/v is equal to the value obtained by dividing the pixelvalue B02 by the number of virtual divided portions, the backgroundcomponent B03/v is equal to the value obtained by dividing the pixelvalue B03 by the number of virtual divided portions, and the backgroundcomponent B04/v is equal to the value obtained by dividing the pixelvalue B04 by the number of virtual divided portions.

More specifically, when the object corresponding to the foreground isstationary, the light corresponding to the foreground object input intothe sensor 11 does not change during the period corresponding to theshutter time. Accordingly, the foreground component F01/v correspondingto the first portion of the shutter time/v from when the shutter hasopened, the foreground component F01/v corresponding to the secondportion of the shutter time/v from when the shutter has opened, theforeground component F01/v corresponding to the third portion of theshutter time/v from when the shutter has opened, and the foregroundcomponent F01/v corresponding to the fourth portion of the shuttertime/v from when the shutter has opened become the same value. The sameapplies to F02/v through F04/v, as in the case of F01/v.

When the object corresponding to the background is stationary, the lightcorresponding to the background object input into the sensor 11 does notchange during the period corresponding to the shutter time. Accordingly,the background component B01/v corresponding to the first portion of theshutter time/v from when the shutter has opened, the backgroundcomponent B01/v corresponding to the second portion of the shuttertime/v from when the shutter has opened, the background component B01/vcorresponding to the third portion of the shutter time/v from when theshutter has opened, and the background component B01/v corresponding tothe fourth portion of the shutter time/v from when the shutter hasopened become the same value. The same applies to B02/v through B04/v.

A description is given of the case in which the object corresponding tothe foreground is moving and the object corresponding to the backgroundis stationary.

FIG. 12 illustrates a model obtained by expanding in the time directionthe pixel-values of the pixels in one line, including a coveredbackground area, when the object corresponding to the foreground ismoving to the right in FIG. 12. In FIG. 12, the amount of movement v is4. Since one frame is a short period, it can be assumed that the objectcorresponding to the foreground is a rigid body moving with constantvelocity. In FIG. 12, the object image corresponding to the foregroundis moving such that it is positioned four pixels to the right withrespect to a reference frame when it is displayed in the subsequentframe.

In FIG. 12, the pixels from the leftmost pixel to the fourth pixelbelong to the foreground area. In FIG. 12, the pixels from the fifthpixel to the seventh pixel from the left belong to the mixed area, whichis the covered background area. In FIG. 12, the rightmost pixel belongsto the background area.

The object corresponding to the foreground is moving such that itgradually covers the object corresponding to the background over time.Accordingly, the components contained in the pixel values of the pixelsbelonging to the covered background area change from the backgroundcomponents to the foreground components at a certain time during theperiod corresponding to the shutter time.

For example, the pixel value M surrounded by the thick frame in FIG. 12is expressed by equation (1) below.M=B 02/v+B 02/v+F 07/v+F 06/v   (1)

For example, the fifth pixel from the left contains a backgroundcomponent corresponding to one portion of the shutter time/v andforeground components corresponding to three portions of the shuttertime/v, and thus, the mixture ratio α of the fifth pixel from the leftis 1/4. The sixth pixel from the left contains background componentscorresponding to two portions of the shutter time/v and foregroundcomponents corresponding to two portions of the shutter time/v, andthus, the mixture ratio α of the sixth pixel from the left is 1/2. Theseventh pixel from the left contains background components correspondingto three portions of the shutter time/v and a foreground componentcorresponding to one portion of the shutter time/v, and thus, themixture ratio α of the fifth pixel from the left is 3/4.

It can be assumed that the object corresponding to the foreground is arigid body, and the foreground object is moving with constant velocitysuch that it is displayed four pixels to the right in the subsequentframe. Accordingly, for example, the foreground component F07/v of thefourth pixel from the left in FIG. 12 corresponding to the first portionof the shutter time/v from when the shutter has opened is equal to theforeground component of the fifth pixel from the left in FIG. 12corresponding to the second portion of the shutter time/v from when theshutter has opened. Similarly, the foreground component F07/v is equalto the foreground component of the sixth pixel from the left in FIG. 12corresponding to the third portion of the shutter time/v from when theshutter has opened, and the foreground component of the seventh pixelfrom the left in FIG. 12 corresponding to the fourth portion of theshutter time/v from when the shutter has opened.

It can be assumed that the object corresponding to the foreground is arigid body, and the foreground object is moving with constant velocitysuch that it is displayed four pixels to the right in the subsequentframe. Accordingly, for example, the foreground component F06/v of thethird pixel from the left in FIG. 12 corresponding to the first portionof the shutter time/v from when the shutter has opened is equal to theforeground component of the fourth pixel from the left in FIG. 12corresponding to the second portion of the shutter time/v from when theshutter has opened. Similarly, the foreground component F06/v is equalto the foreground component of the fifth pixel from the left in FIG. 12corresponding to the third portion of the shutter time/v from when theshutter has opened, and the foreground component of the sixth pixel fromthe left in FIG. 12 corresponding to the fourth portion of the shuttertime/v from when the shutter has opened.

It can be assumed that the object corresponding to the foreground is arigid body, and the foreground object is moving with constant velocitysuch that it is displayed four pixels to the right in the subsequentframe. Accordingly, for example, the foreground component F05/v of thesecond pixel from the left in FIG. 12 corresponding to the first portionof the shutter time/v from when the shutter has opened is equal to theforeground component of the third pixel from the left in FIG. 12corresponding to the second portion of the shutter time/v from when theshutter has opened. Similarly, the foreground-component F05/v is equalto the foreground component of the fourth pixel from the left in FIG. 12corresponding to the third portion of the shutter time/v from when theshutter has opened, and the foreground component of the fifth pixel fromthe left in FIG. 12 corresponding to the fourth portion of the shuttertime/v from when the shutter has opened.

It can be assumed that the object corresponding to the foreground is arigid body, and the foreground object is moving with constant velocitysuch that it is displayed four pixels to the right in the subsequentframe. Accordingly, for example, the foreground component F04/v of theleft most pixel in FIG. 12 corresponding to the first portion of theshutter time/v from when the shutter has opened is equal to theforeground component of the second pixel from the left in FIG. 12corresponding to the second portion of the shutter time/v from when theshutter has opened. Similarly, the foreground component F04/v is equalto the foreground component of the third pixel from the left in FIG. 12corresponding to the third portion of the shutter time/v from when theshutter has opened, and the foreground component of the fourth pixelfrom the left in FIG. 12 corresponding to the fourth portion of theshutter time/v from when the shutter has opened.

Since the foreground area corresponding to the moving object containsmotion blur as discussed above, it can also be referred to as a“distortion area”.

FIG. 13 illustrates a model obtained by expanding in the time directionthe pixel values of the pixels in one line including an uncoveredbackground area when the object corresponding to the foreground ismoving to the right in FIG. 13. In FIG. 13, the amount of movement v is4. Since one frame is a short period, it can be assumed that the objectcorresponding to the foreground is a rigid body moving with constantvelocity. In FIG. 13, the object image corresponding to the foregroundis moving to the right such that it is positioned four pixels to theright with respect to a reference frame when it is displayed in thesubsequent frame.

In FIG. 13, the pixels from the leftmost pixel to the fourth pixelbelong to the background area. In FIG. 13, the pixels from the fifthpixel to the seventh pixels from the left belong to the mixed area,which is an uncovered background area. In FIG. 13, the rightmost pixelbelongs to the foreground area.

The object corresponding to the foreground which covers the objectcorresponding to the background is moving such that it is graduallyremoved from the object corresponding to the background over time.Accordingly, the components contained in the pixel values of the pixelsbelonging to the uncovered background area change from the foregroundcomponents to the background components at a certain time of the periodcorresponding to the shutter time.

For example, the pixel value M′ surrounded by the thick frame in FIG. 13is expressed by equation (2).M′=F 02/v+F 01/v+B 26/v+B 26/v   (2)

For example, the fifth pixel from the left contains backgroundcomponents corresponding to three portions of the shutter time/v and aforeground component corresponding to one shutter portion of the shuttertime/v, and thus, the mixture ratio α of the fifth pixel from the leftis 3/4. The sixth pixel from the left contains background componentscorresponding to two portions of the shutter time/v and foregroundcomponents corresponding to two portions of the shutter time/v, andthus, the mixture ratio α of the sixth pixel from the left is 1/2. Theseventh pixel from the left contains a background componentcorresponding to one portion of the shutter time/v and foregroundcomponents corresponding to three portions of the shutter time/v, andthus, the mixture ratio α of the seventh pixel from the left is 1/4.

When equations (1) and (2) are generalized, the pixel value M can beexpressed by equation (3): $\begin{matrix}{M = {{\alpha \cdot B} + {\sum\limits_{i}{{Fi}/v}}}} & (3)\end{matrix}$where α is the mixture ratio, B indicates a pixel value of thebackground, and Fi/v designates a foreground component.

It can be assumed that the object corresponding to the foreground is arigid body, which is moving with constant velocity, and the amount ofmovement is 4. Accordingly, for example, the foreground component F01/vof the fifth pixel from the left in FIG. 13 corresponding to the firstportion of the shutter time/v from when the shutter has opened is equalto the foreground component of the sixth pixel from the left in FIG. 13corresponding to the second portion of the shutter time/v from when theshutter has opened. Similarly, the foreground component F01/v is equalto the foreground component of the seventh pixel from the left in FIG.13 corresponding to the third portion of the shutter time/v from whenthe shutter has opened, and the foreground component of the eighth pixelfrom the left in FIG. 13 corresponding to the fourth portion of theshutter time/v from when the shutter has opened.

It can be assumed that the object corresponding to the foreground is arigid body, which is moving with constant velocity, and the amount ofmovement v is 4. Accordingly, for example, the foreground componentF02/v of the sixth pixel from the left in FIG. 13 corresponding to thefirst portion of the shutter time/v from when the shutter has opened isequal to the foreground component of the seventh pixel from the left inFIG. 13 corresponding to the second portion of the shutter time/v fromwhen the shutter has opened. Similarly, the foreground component F02/vis equal to the foreground component of the eighth pixel from the leftin FIG. 13 corresponding to the third portion of the shutter time/v fromwhen the shutter has opened.

It can be assumed that the object corresponding to the foreground is arigid body, which is moving with constant velocity, and the amount ofmovement v is 4. Accordingly, for example, the foreground componentF03/v of the seventh pixel from the left in FIG. 13 corresponding to thefirst portion of the shutter time/v from when the shutter has opened isequal to the foreground component of the eighth pixel from the left inFIG. 13 corresponding to the second portion of the shutter time/v fromwhen the shutter has opened.

It has been described with reference to FIGS. 11 through 13 that thenumber of virtual divided portions is 4. The number of virtual dividedportions corresponds to the amount of movement v. Generally, the amountof movement v corresponds to the moving speed of the objectcorresponding to the foreground. For example, if the objectcorresponding to the foreground is moving such that it is displayed fourpixels to the right with respect to a certain frame when it ispositioned in the subsequent frame, the amount of movement v is set to4. The number of virtual divided portions is set to 4 in accordance withthe amount of movement v. Similarly, when the object corresponding tothe foreground is moving such that it is displayed six pixels to theleft with respect to a certain frame when it is positioned in thesubsequent frame, the amount of movement v is set to 6, and the numberof virtual divided portions is set to 6.

FIGS. 14 and 15 illustrate the relationship of the foreground area, thebackground area, and the mixed area which consists of a coveredbackground or an uncovered background, which are discussed above, to theforeground components and the background components corresponding to thedivided periods of the shutter time.

FIG. 14 illustrates an example in which pixels in the foreground area,the background area, and the mixed area are extracted from an imagecontaining a foreground corresponding to an object moving in front of astationary background. In the example shown in FIG. 14, the objectcorresponding to the foreground is horizontally moving with respect tothe screen.

Frame #n+1 is a frame subsequent to frame #n, and frame #n+2 is a framesubsequent to frame #n+1.

Pixels in the foreground area, the background area, and the mixed areaare extracted from one of frames #n through #n+2, and the amount ofmovement v is set to 4. A model obtained by expanding the pixel valuesof the extracted pixels in the time direction is shown in FIG. 15.

Since the object corresponding to the foreground is moving, the pixelvalues in the foreground area are formed of four different foregroundcomponents corresponding to the shutter time/v. For example, theleftmost pixel of the pixels in the foreground area shown in FIG. 15consists of F01/v, F02/v, F03/v, and F04/v. That is, the pixels in theforeground contain motion blur.

Since the object corresponding to the background is stationary, lightinput into the sensor 11 corresponding to the background during theshutter time does not change. In this case, the pixel values in thebackground area do not contain motion blur.

The pixel values in the mixed area consisting of a covered backgroundarea or an uncovered background area are formed of foreground componentsand background components.

A description is given below of a model obtained by expanding in thetime direction the pixel values of the pixels which are alignedside-by-side in a plurality of frames and which are located at the samepositions when the frames are overlapped when the image corresponding tothe object is moving. For example, when the image corresponding to theobject is moving horizontally with respect to the screen, pixels alignedon the screen can be selected as the pixels aligned side-by-side.

FIG. 16 illustrates a model obtained by expanding in the time directionthe pixels which are aligned side-by-side in three frames of an imageobtained by capturing an object corresponding to a stationary backgroundand which are located at the same positions when the frames areoverlapped. Frame #n is the frame subsequent to frame #n−1, and frame#n+1 is the frame subsequent to frame #n. The same applies to the otherframes.

The pixel values B01 through B12 shown in FIG. 16 are pixel valuescorresponding to the stationary background object. Since the objectcorresponding to the background is stationary, the pixel values of thecorresponding pixels in frame #n−1 through frame #n+1 do not change. Forexample, the pixel in frame #n and the pixel in frame #n+1 located atthe corresponding position of the pixel having the pixel value B05 inframe #n−1 have the pixel value B05.

FIG. 17 illustrates a model obtained by expanding in the time directionthe pixels which are aligned side-by-side in three frames of an imageobtained by capturing an object corresponding to a foreground that ismoving to the right in FIG. 17 together with an object corresponding toa stationary background and which are located at the same positions whenthe frames are overlapped. The model shown in FIG. 17 contains a coveredbackground area.

In FIG. 17, it can be assumed that the object corresponding to theforeground is a rigid body moving with constant velocity, and that it ismoving such that it is displayed four pixels to the right in thesubsequent frame. Accordingly, the amount of movement v is 4, and thenumber of virtual divided portions is 4.

For example, the foreground component of the leftmost pixel of frame#n−1 in FIG. 17 corresponding to the first portion of the shutter time/vfrom when the shutter has opened is F12/v, and the foreground componentof the second pixel from the left in FIG. 17 corresponding to the secondportion of the shutter time/v from when the shutter has opened is alsoF12/v. The foreground component of the third pixel from the left in FIG.17 corresponding to the third portion of the shutter time/v from whenthe shutter has opened and the foreground component of the fourth pixelfrom the left in FIG. 17 corresponding to the fourth portion of theshutter time/v from when the shutter has opened are F12/v.

The foreground component of the leftmost pixel of frame #n−1 in FIG. 17corresponding to the second portion of the shutter time/v from when theshutter has opened is F11/v. The foreground component of the secondpixel from the left in FIG. 17 corresponding to the third portion of theshutter time/v from when the shutter has opened is also F11/v. Theforeground component of the third pixel from the left in FIG. 17corresponding to the fourth portion of the shutter time/v from when theshutter has opened is F11/v.

The foreground component of the leftmost pixel of frame #n−1 in FIG. 17corresponding to the third portion of the shutter time/v from when theshutter has opened is F10/v. The foreground component of the secondpixel from the left in FIG. 17 corresponding to the fourth portion ofthe shutter time/v from when the shutter has opened is also F10/v. Theforeground component of the leftmost pixel of frame #n−1 in FIG. 17corresponding to the fourth portion of the shutter time/v from when theshutter has opened is F09/v.

Since the object corresponding to the background is stationary, thebackground component of the second pixel from the left of frame #n−1 inFIG. 17 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is B01/v. The background components of thethird pixel from the left of frame #n−1 in FIG. 17 corresponding to thefirst and second portions of the shutter time/v from when the shutterhas opened are B02/v. The background components of the fourth pixel fromthe left of frame #n−1 in FIG. 17 corresponding to the first throughthird portions of the shutter time/v from when the shutter has openedare B03/v.

In frame #n−1 in FIG. 17, the leftmost pixel from the left belongs tothe foreground area, and the second through fourth pixels from the leftbelong to the mixed area, which is a covered background area.

The fifth through twelfth pixels from the left of frame #n−1 in FIG. 17belong to the background area, and the pixel values thereof are B04through B11, respectively.

The first through fifth pixels from the left in frame #n in FIG. 17belong to the foreground area. The foreground component in the shuttertime/v in the foreground area of frame #n is any one of F05/v throughF12/v.

It can be assumed that the object corresponding to the foreground is arigid body moving with constant velocity, and that it is moving suchthat the foreground image is displayed four pixels to the right in thesubsequent frame. Accordingly, the foreground component of the fifthpixel from the left of frame #n in FIG. 17 corresponding to the firstportion of the shutter time/v from when the shutter has opened is F12/v,and the foreground component of the sixth pixel from the left in FIG. 17corresponding to the second portion of the shutter time/v from when theshutter has opened is also F12/v. The foreground component of theseventh pixel from the left in FIG. 17 corresponding to the thirdportion of the shutter time/v from when the shutter has opened and theforeground component of the eighth pixel from the left in FIG. 17corresponding to the fourth portion of the shutter time/v from when theshutter has opened are F12/v.

The foreground component of the fifth pixel from the left of frame #n inFIG. 17 corresponding to the second portion of the shutter time/v fromwhen the shutter has opened is F11/v. The foreground component of thesixth pixel from the left in FIG. 17 corresponding to the third portionof the shutter time/v from when the shutter has opened is also F11/v.The foreground component of the seventh pixel from the left in FIG. 17corresponding to the fourth portion of the shutter time/v from when theshutter has opened is F11/v.

The foreground component of the fifth pixel from the left of frame #n inFIG. 17 corresponding to the third portion of the shutter time/v fromwhen the shutter has opened is F10/v. The foreground component of thesixth pixel from the left in FIG. 17 corresponding to the fourth portionof the shutter time/v from when the shutter has opened is also F10/v.The foreground component of the fifth pixel from the left of frame #n inFIG. 17 corresponding to the fourth portion of the shutter time/v fromwhen the shutter has opened is F09/v.

Since the object corresponding to the background is stationary, thebackground component of the sixth pixel from the left of frame #n inFIG. 17 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is B05/v. The background components of theseventh pixel from the left of frame #n in FIG. 17 corresponding to thefirst and second portions of the shutter time/v from when the shutterhas opened are B06/v. The background components of the eighth pixel fromthe left of frame #n in FIG. 17 corresponding to the first through thirdportion of the shutter time/v from when the shutter has opened areB07/v.

In frame #n in FIG. 17, the sixth through eighth pixels from the leftbelong to the mixed area, which is a covered background area.

The ninth through twelfth pixels from the left of frame #n in FIG. 17belong to the background area, and the pixel values thereof are B08through B11, respectively.

The first through ninth pixels from the left in frame #n+1 in FIG. 17belong to the foreground area. The foreground component in the shuttertime/v in the foreground area of frame #n+1 is any one of F01/v throughF12/v.

It can be assumed that the object corresponding to the foreground is arigid body moving with constant velocity, and that it is moving suchthat the foreground image is displayed four pixels to the right in thesubsequent frame. Accordingly, the foreground component of the ninthpixel from the left of frame #n+1 in FIG. 17 corresponding to the firstportion of the shutter time/v from when the shutter has opened is F12/v,and the foreground component of the tenth pixel from the left in FIG. 17corresponding to the second portion of the shutter time/v from when theshutter has opened is also F12/v. The foreground component of theeleventh pixel from the left in FIG. 17 corresponding to the thirdportion of the shutter time/v from when the shutter has opened and theforeground component of the twelfth pixel from the left in FIG. 17corresponding to the fourth portion of the shutter time/v from when theshutter has opened are F12/v.

The foreground component of the ninth pixel from the left of frame #n+1in FIG. 17 corresponding to the second portion of the shutter time/vfrom when the shutter has opened is F11/v. The foreground component ofthe tenth pixel from the left in FIG. 17 corresponding to the thirdportion of the shutter time/v from when the shutter has opened is alsoF11/v. The foreground component of the eleventh pixel from the left inFIG. 17 corresponding to the fourth portion of the shutter time/v fromwhen the shutter has opened is F11/v.

The foreground component of the ninth pixel from the left of frame #n+1in FIG. 17 corresponding to the third portion of the shutter time/v fromwhen the shutter has opened is F10/v. The foreground component of thetenth pixel from the left in FIG. 17 corresponding to the fourth portionof the shutter time/v from when the shutter has opened is also F10/v.The foreground component of the ninth pixel from the left of frame #n+1in FIG. 17 corresponding to the fourth portion of the shutter time/vfrom when the shutter has opened is F09/v.

Since the object corresponding to the background is stationary, thebackground component of the tenth pixel from the left of frame #n+1 inFIG. 17 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is B09/v. The background components of theeleventh pixel from the left of frame #n+1 in FIG. 17 corresponding tothe first and second portions of the shutter time/v from when theshutter has opened are B10/v. The background components of the twelfthpixel from the left of frame #n+1 in FIG. 17 corresponding to the firstthrough third portion of the shutter time/v from when the shutter hasopened are B11/v.

In frame #n+1 in FIG. 17, the tenth through twelfth pixels from the leftbelong to the mixed area, which is a covered background area.

FIG. 18 is a model of an image obtained by extracting the foregroundcomponents from the pixel values shown in FIG. 17.

FIG. 19 illustrates a model obtained by expanding in the time directionthe pixels which are aligned side-by-side in three frames of an imageobtained by capturing an object corresponding to a foreground that ismoving to the right in FIG. 19 together with an object corresponding toa stationary background and which are located at the same positions whenthe frames are overlapped. The model shown in FIG. 19 contains anuncovered background area.

In FIG. 19, it can be assumed that the object corresponding to theforeground is a rigid body moving with constant velocity, and that it ismoving such that it is displayed four pixels to the right in thesubsequent frame. Accordingly, the amount of movement v is 4.

For example, the foreground component of the leftmost pixel of frame#n−1 in FIG. 19 corresponding to the first portion of the shutter time/vfrom when the shutter has opened is F13/v, and the foreground componentof the second pixel from the left in FIG. 19 corresponding to the secondportion of the shutter time/v from when the shutter has opened is alsoF13/v. The foreground component of the third pixel from the left in FIG.19 corresponding to the third portion of the shutter time/v from whenthe shutter has opened and the foreground component of the fourth pixelfrom the left in FIG. 19 corresponding to the fourth portion of theshutter time/v from when the shutter has opened are F13/v.

The foreground component of the second pixel from the left of frame #n−1in FIG. 19 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is F14/v. The foreground component of thethird pixel from the left in FIG. 19 corresponding to the second portionof the shutter time/v from when the shutter has opened is also F14/v.The foreground component of the third pixel from the left in FIG. 19corresponding to the first portion of the shutter time/v from when theshutter has opened is F15/v.

Since the object corresponding to the background is stationary, thebackground components of the leftmost pixel of frame #n−1 in FIG. 19corresponding to the second through fourth portions of the shuttertime/v from when the shutter has opened are B25/v. The backgroundcomponents of the second pixel from the left of frame #n−1 in FIG. 19corresponding to the third and fourth portions of the shutter time/vfrom when the shutter has opened are B26/v. The background component ofthe third pixel from the left of frame #n−1 in FIG. 19 corresponding tothe fourth portion of the shutter time/v from when the shutter hasopened is B27/v.

In frame #n−1 in FIG. 19, the leftmost pixel through the third pixelbelong to the mixed area, which is an uncovered background area.

The fourth through twelfth pixels from the left of frame #n−1 in FIG. 19belong to the foreground area. The foreground component of the frame isany one of F13/v through F24/v.

The leftmost pixel through the fourth pixel from the left of frame #n inFIG. 19 belong to the background area, and the pixel values thereof areB25 through B28, respectively.

It can be assumed that the object corresponding to the foreground is arigid body moving with constant velocity, and that it is moving suchthat it is displayed four pixels to the right in the subsequent frame.Accordingly, the foreground component of the fifth pixel from the leftof frame #n in FIG. 19 corresponding to the first portion of the shuttertime/v from when the shutter has opened is F13/v, and the foregroundcomponent of the sixth pixel from the left in FIG. 19 corresponding tothe second portion of the shutter time/v from when the shutter hasopened is also F13/v. The foreground component of the seventh pixel fromthe left in FIG. 19 corresponding to the third portion of the shuttertime/v from when the shutter has opened and the foreground component ofthe eighth pixel from the left in FIG. 19 corresponding to the fourthportion of the shutter time/v from when the shutter has opened areF13/v.

The foreground component of the sixth pixel from the left of frame #n inFIG. 19 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is F14/v. The foreground component of theseventh pixel from the left in FIG. 19 corresponding to the secondportion of the shutter time/v from when the shutter has opened is alsoF14/v. The foreground component of the eighth pixel from the left inFIG. 19 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is F15/v.

Since the object corresponding to the background is stationary, thebackground components of the fifth pixel from the left of frame #n inFIG. 19 corresponding to the second through fourth portions of theshutter time/v from when the shutter has opened are B29/v. Thebackground components of the sixth pixel from the left of frame #n inFIG. 19 corresponding to the third and fourth portions of the shuttertime/v from when the shutter has opened are B30/v. The backgroundcomponent of the seventh pixel from the left of frame #n in FIG. 19corresponding to the fourth portion of the shutter time/v from when theshutter has opened is B31/v.

In frame #n in FIG. 19, the fifth pixel through the seventh pixel fromthe left belong to the mixed area, which is an uncovered backgroundarea.

The eighth through twelfth pixels from the left of frame #n in FIG. 19belong to the foreground area. The value in the foreground area of frame#n corresponding to the period of the shutter time/v is any one of F13/vthrough F20/v.

The leftmost pixel through the eighth pixel from the left of frame #n+1in FIG. 19 belong to the background area, and the pixel values thereofare B25 through B32, respectively.

It can be assumed that the object corresponding to the foreground is arigid body moving with constant velocity, and that it is moving suchthat it is displayed four pixels to the right in the subsequent frame.Accordingly, the foreground component of the ninth pixel from the leftof frame #n+1 in FIG. 19 corresponding to the first portion of theshutter time/v from when the shutter has opened is F13/v, and theforeground component of the tenth pixel from the left in FIG. 19corresponding to the second portion of the shutter time/v from when theshutter has opened is also F13/v. The foreground component of theeleventh pixel from the left in FIG. 19 corresponding to the thirdportion of the shutter time/v from when the shutter has opened and theforeground component of the twelfth pixel from the left in FIG. 19corresponding to the fourth portion of the shutter time/v from when theshutter has opened are F13/v.

The foreground component of the tenth pixel from the left of frame #n+1in FIG. 19 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is F14/v. The foreground component of theeleventh pixel from the left in FIG. 19 corresponding to the secondportion of the shutter time/v from when the shutter has opened is alsoF14/v. The foreground component of the twelfth pixel from the left inFIG. 19 corresponding to the first portion of the shutter time/v fromwhen the shutter has opened is F15/v.

Since the object corresponding to the background is stationary, thebackground components of the ninth pixel from the left of frame #n+1 inFIG. 19 corresponding to the second through fourth portions of theshutter time/v from when the shutter has opened are B33/v. Thebackground components of the tenth pixel from the left of frame #n+1 inFIG. 19 corresponding to the third and fourth portions of the shuttertime/v from when the shutter has opened are B34/v. The backgroundcomponent of the eleventh pixel from the left of frame #n+1 in FIG. 19corresponding to the fourth portion of the shutter time/v from when theshutter has opened is B35/v.

In frame #n+1 in FIG. 19, the ninth through eleventh pixels from theleft in FIG. 19 belong to the mixed area, which is an uncoveredbackground area.

The twelfth pixel from the left of frame #n+1 in FIG. 19 belongs to theforeground area. The foreground component in the shutter time/v in theforeground area of frame #n+1 is any one of F13 through F16,respectively.

FIG. 20 illustrates a model of an image obtained by extracting theforeground components from the pixel values shown in FIG. 19.

Referring back to FIG. 4, the area specifying unit 103 specifies flagsindicating to which of a foreground area, a background area, a coveredbackground area, or an uncovered background area the individual pixelsof the input image belong by using the pixel values of a plurality offrames, and supplies the flags to the mixture-ratio calculator 104 andthe motion-blur adjusting unit 106 as the area information.

The mixture-ratio calculator 104 calculates the mixture ratio α for eachpixel contained in the mixed area based on the pixel values of aplurality of frames and the area information, and supplies thecalculated mixture ratio α to the foreground/background separator 105.

The foreground/background separator 105 extracts the foregroundcomponent image consisting of only the foreground components based onthe pixel values of a plurality of frames, the area information, and themixture ratio α, and supplies the foreground component image to themotion-blur adjusting unit 106.

The motion-blur adjusting unit 106 adjusts the amount of motion blurcontained in the foreground component image based on the foregroundcomponent image supplied from the foreground/background separator 105,the motion vector supplied from the motion detector 102, and the areainformation supplied from the area specifying unit 103, and then outputsthe foreground component image in which motion blur is adjusted.

The processing for adjusting the amount of motion blur performed by thesignal processor 12 is described below with reference to the flowchartof FIG. 21. In step S11, the area specifying unit 103 executes areaspecifying processing, based on an input image, for generating areainformation indicating to which of a foreground area, a background area,a covered background area, or an uncovered background area each pixel ofthe input image belongs. Details of the area specifying processing aregiven below. The area specifying unit 103 supplies the generated areainformation to the mixture-ratio calculator 104.

In step S11, the area specifying unit 103 may generate, based on theinput image, area information indicating to which of the foregroundarea, the background area, or the mixed area (regardless of whether eachpixel belongs to a covered background area or an uncovered backgroundarea) each pixel of the input image belongs. In this case, theforeground/background separator 105 and the motion-blur adjusting unit106 determine based on the direction of the motion vector whether themixed area is a covered background area or an uncovered background area.For example, if the input image is disposed in the order of theforeground area, the mixed area, and the background area in thedirection of the motion vector, it is determined that the mixed area isa covered background area. If the input image is disposed in the orderof the background area, the mixed area, and the foreground area in thedirection of the motion vector, it is determined that the mixed area isan uncovered background area.

In step S12, the mixture-ratio calculator 104 calculates the mixtureratio α for each pixel contained in the mixed area based on the inputimage, the motion vector and the positional information thereof, and thearea information. Details of the mixture ratio calculating processingare given below. The mixture-ratio calculator 104 supplies thecalculated mixture ratio α to the foreground/background separator 105.

In step S13, the foreground/background separator 105 extracts theforeground components from the input image based on the area informationand the mixture ratio α, and supplies the foreground components to themotion-blur adjusting unit 106 as the foreground component image.

In step S14, the motion-blur adjusting unit 106 generates, based on themotion vector and the area information, the unit of processing thatindicates the positions of consecutive pixels disposed in the movingdirection and belonging to any of the uncovered background area, theforeground area, and the covered background area, and adjusts the amountof motion blur contained in the foreground components corresponding tothe unit of processing. Details of the processing for adjusting theamount of motion blur are given below.

In step S15, the signal processor 12 determines whether the processingis finished for the whole screen. If it is determined that theprocessing is not finished for the whole screen, the process proceeds tostep S14, and the processing for adjusting the amount of motion blur forthe foreground components corresponding to the unit of processing isrepeated.

If it is determined in step S15 that the processing is finished for thewhole screen, the processing is completed.

In this manner, the signal processor 12 is capable of adjusting theamount of motion blur contained in the foreground by separating theforeground and the background. That is, the signal processor 12 iscapable of adjusting the amount of motion blur contained in sampled dataindicating the pixel values of the foreground pixels.

The configuration of each of the area specifying unit 103, themixture-ratio calculator 104, the foreground/background separator 105,and the motion-blur adjusting unit 106 is described below.

FIG. 22 is a block diagram illustrating an example of the configurationof the area specifying unit 103. The area specifying unit 103 shown inFIG. 22 does not use a motion vector. A frame memory 201 stores an inputimage in units of frames. When the image to be processed is frame #n,the frame memory 201 stores frame #n−2, which is the frame two framesbefore frame #n, frame #n−1, which is the frame one frame before frame#n, frame #n, frame #n+1, which is the frame one frame after frame #n,frame #n+2, which is the frame two frames after frame #n.

A stationary/moving determining portion 202-1 reads the pixel value ofthe pixel of frame #n+2 located at the same position as a designatedpixel of frame #n in which the area to which the pixel belongs isdetermined, and reads the pixel value of the pixel of frame #n+1 locatedat the same position of the designated pixel of frame #n from the framememory 201, and calculates the absolute value of the difference betweenthe read pixel values. The stationary/moving determining portion 202-1determines whether the absolute value of the difference between thepixel value of frame #n+2 and the pixel value of frame #n+1 is greaterthan a preset threshold Th. If it is determined that the difference isgreater than the threshold Th, a stationary/moving determinationindicating “moving” is supplied to an area determining portion 203-1. Ifit is determined that the absolute value of the difference between thepixel value of the pixel of frame #n+2 and the pixel value of the pixelof frame #n+1 is smaller than or equal to the threshold Th, thestationary/moving determining portion 202-1 supplies a stationary/movingdetermination indicating “stationary” to the area determining portion203-1.

A stationary/moving determining portion 202-2 reads the pixel value of adesignated pixel of frame #n in which the area to which the pixelbelongs is determined, and reads the pixel value of the pixel of frame#n+1 located at the same position as the designated pixel of frame #nfrom the frame memory 201, and calculates the absolute value of thedifference between the pixel values. The stationary/moving determiningportion 202-2 determines whether the absolute value of the differencebetween the pixel value of frame #n+1 and the pixel value of frame #n isgreater than a preset threshold Th. If it is determined that theabsolute value of the difference between the pixel values is greaterthan the threshold Th, a stationary/moving determination indicating“moving” is supplied to the area determining portion 203-1 and an areadetermining portion 203-2. If it is determined that the absolute valueof the difference between the pixel value of the pixel of frame #n+1 andthe pixel value of the pixel of frame #n is smaller than or equal to thethreshold Th, the stationary/moving determining portion 202-2 supplies astationary/moving determination indicating “stationary” to the areadetermining portion 203-1 and the area determining portion 203-2.

A stationary/moving determining portion 202-3 reads the pixel value of adesignated pixel of frame #n in which the area to which the pixelbelongs is determined, and reads the pixel value of the pixel of frame#n−1 located at the same position as the designated pixel of frame #nfrom the frame memory 201, and calculates the absolute value of thedifference between the pixel values. The stationary/moving determiningportion 202-3 determines whether the absolute value of the differencebetween the pixel value of frame #n and the pixel value of frame #n−1 isgreater than a preset threshold Th. If it is determined that theabsolute value of the difference between the pixel values is greaterthan the threshold Th, a stationary/moving determination indicating“moving” is supplied to the area determining portion 203-2 and an areadetermining portion 203-3. If it is determined that the absolute valueof the difference between the pixel value of the pixel of frame #n andthe pixel value of the pixel of frame #n−1 is smaller than or equal tothe threshold Th, the stationary/moving determining portion 202-3supplies a stationary/moving determination indicating “stationary” tothe area determining portion 203-2 and the area determining portion203-3.

A stationary/moving determining portion 202-4 reads the pixel value ofthe pixel of frame #n−1 located at the same position as a designatedpixel of frame #n in which the area to which the pixel belongs isdetermined, and reads the pixel value of the pixel of frame #n−2 locatedat the same position as the designated pixel of frame #n from the framememory 201, and calculates the absolute value of the difference betweenthe pixel values. The stationary/moving determining portion 202-4determines whether the absolute value of the difference between thepixel value of frame #n−1 and the pixel value of frame #n−2 is greaterthan a preset threshold Th. If it is determined that the absolute valueof the difference between the pixel values is greater than the thresholdTh, a stationary/moving determination indicating “moving” is supplied tothe area determining portion 203-3. If it is determined that theabsolute value of the difference between the pixel value of the pixel offrame #n−1 and the pixel value of the pixel of frame #n−2 is smallerthan or equal to the threshold Th, the stationary/moving determiningportion 202-4 supplies a stationary/moving determination indicating“stationary” to the area determining portion 203-3.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-1 indicates “stationary” andwhen the stationary/moving determination supplied from thestationary/moving determining portion 202-2 indicates “moving”, the areadetermining portion 203-1 determines that the designated pixel of frame#n belongs to an uncovered background area, and sets “1”, whichindicates that the designated pixel belongs to an uncovered backgroundarea, in an uncovered-background-area determining flag associated withthe designated pixel.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-1 indicates “moving” or whenthe stationary/moving determination supplied from the stationary/movingdetermining portion 202-2 indicates “stationary”, the area specifyingunit 203-1 determines that the designated pixel of frame #n does notbelong to an uncovered background area, and sets “0”, which indicatesthat the designated pixel does not belong to an uncovered backgroundarea, in the uncovered-background-area determining flag associated withthe designated pixel.

The area determining portion 203-1 supplies theuncovered-background-area determining flag in which “1” or “0” is set asdiscussed above to a determining-flag-storing frame memory 204.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-2 indicates “stationary” andwhen the stationary/moving determination supplied from thestationary/moving determining portion 202-3 indicate “stationary”, thearea determining portion 203-2 determines that the designated pixel offrame #n belongs to the stationary area, and sets “1”, which indicatesthat the pixel belongs to the stationary area, in a stationary-areadetermining flag associated with the designated pixel.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-2 indicates “moving” or whenthe stationary/moving determination supplied from the stationary/movingdetermining portion 202-3 indicate “moving”, the area determiningportion 203-2 determines that the designated pixel of frame #n does notbelong to the stationary area, and sets “0”, which indicates that thepixel does not belong to the stationary area, in the stationary-areadetermining flag associated with the designated pixel.

The area determining portion 203-2 supplies the stationary-areadetermining flag in which “1” or “0” is set as discussed above to thedetermining-flag-storing frame memory 204.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-2 indicates “moving” and whenthe stationary/moving determination supplied from the stationary/movingdetermining portion 202-3 indicate “moving”, the area determiningportion 203-2 determines that the designated pixel of frame #n belongsto the moving area, and sets “1”, which indicates that the designatedpixel belongs to the moving area, in a moving-area determining flagassociated with the designated pixel.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-2 indicates “stationary” orwhen the stationary/moving determination supplied from thestationary/moving determining portion 202-3 indicate “stationary”, thearea determining portion 203-2 determines that the designated pixel offrame #n does not belong to the moving area, and sets “0”, whichindicates that the pixel does not belong to the moving area, in themoving-area determining flag associated with the designated pixel.

The area determining portion 203-2 supplies the moving-area determiningflag in which “1” or “0” is set as discussed above to thedetermining-flag-storing frame memory 204.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-3 indicates “moving” and whenthe stationary/moving determination supplied from the stationary/movingdetermining portion 202-4 indicate “stationary”, the area determiningportion 203-3 determines that the designated pixel of frame #n belongsto a covered background area, and sets “1”, which indicates that thedesignated pixel belongs to the covered background area, in acovered-background-area determining flag associated with the designatedpixel.

When the stationary/moving determination supplied from thestationary/moving determining portion 202-3 indicates “stationary” orwhen the stationary/moving determination supplied from thestationary/moving determining portion 202-4 indicate “moving”, the areadetermining portion 203-3 determines that the designated pixel of frame#n does not belong to a covered background area, and sets “0”, whichindicates that the designated pixel does not belong to a coveredbackground area, in the covered-background-area determining flagassociated with the designated pixel.

The area determining portion 203-3 supplies the covered-background-areadetermining flag in which “1” or “0” is set as discussed above to thedetermining-flag-storing frame memory 204.

The determining-flag-storing frame memory 204 thus stores theuncovered-background-area determining flag supplied from the areadetermining portion 203-1, the stationary-area determining flag suppliedfrom the area determining portion 203-2, the moving-area determiningflag supplied from the area determining portion 203-2, and thecovered-background-area determining flag supplied from the areadetermining portion 203-3.

The determining-flag-storing frame memory 204 supplies theuncovered-background-area determining flag, the stationary-areadetermining flag, the moving-area determining flag, and thecovered-background-area determining flag stored therein to a synthesizer205. The synthesizer 205 generates area information indicating to whichof the uncovered background area, the stationary area, the moving area,or the covered background area each pixel belongs based on theuncovered-background-area determining flag, the stationary-areadetermining flag, the moving-area determining flag, and thecovered-background-area determining flag supplied from thedetermining-flag-storing frame memory 204, and supplies the areainformation to a determining-flag-storing frame memory 206.

The determining-flag-storing frame memory 206 stores the areainformation supplied from the synthesizer 205, and also outputs the areainformation stored therein.

An example of the processing performed by the area specifying unit 103is described below with reference to FIGS. 23 through 27.

When the object corresponding to the foreground is moving, the positionof the image corresponding to the object on the screen changes in everyframe. As shown in FIG. 23, the image corresponding to the objectlocated at the position indicated by Yn(x,y) in frame #n is positionedat Yn+1(x,y) in frame #n+1, which is subsequent to frame #n.

A model obtained by expanding in the time direction the pixel values ofthe pixels aligned side-by-side in the moving direction of the imagecorresponding to the foreground object is shown in FIG. 24. For example,if the moving direction of the image corresponding to the foregroundobject is horizontal with respect to the screen, the model shown in FIG.24 is a model obtained by expanding in the time direction the pixelvalues of the pixels disposed on a line side-by-side.

In FIG. 24, the line in frame #n is equal to the line in frame #n+1.

The foreground components corresponding to the object contained in thesecond pixel to the thirteenth pixel from the left in frame #n arecontained in the sixth pixel through the seventeenth pixel from the leftin frame #n+1.

In frame #n, the pixels belonging to the covered background area are theeleventh through thirteenth pixels from the left, and the pixelsbelonging to the uncovered background area are the second through fourthpixels from the left. In frame #n+1, the pixels belonging to the coveredbackground area are the fifteenth through seventeenth pixels from theleft, and the pixels belonging to the uncovered background area are thesixth through eighth pixels from the left.

In the example shown in FIG. 24, since the foreground componentscontained in frame #n are moved by four pixels in frame #n+1, the amountof movement v is 4. The number of virtual divided portions is 4 inaccordance with the amount of movement v.

A description is now given of a change in pixel values of the pixelsbelonging to the mixed area in the frames before and after a designatedframe.

In FIG. 25, the pixels belonging to a covered background area in frame#n in which the background is stationary and the amount of movement v inthe foreground is 4 are the fifteenth through seventeenth pixels fromthe left. Since the amount of movement v is 4, the fifteenth throughseventeenth frames from the left in the previous frame #n−1 contain onlybackground components and belong to the background area. The fifteenththrough seventeenth pixels from the left in frame #n−2, which is onebefore frame #n−1, contain only background components and belong to thebackground area.

Since the object corresponding to the background is stationary, thepixel value of the fifteenth pixel from the left in frame #n−1 does notchange from the pixel value of the fifteenth pixel from the left inframe #n−2. Similarly, the pixel value of the sixteenth pixel from theleft in frame #n−1 does not change from the pixel value of the sixteenthpixel from the left in frame #n−2, and the pixel value of theseventeenth pixel from the left in frame #n−1 does not change from thepixel value of the seventeenth pixel from the left in frame #n−2.

That is, the pixels in frame #n−1 and frame #n−2 corresponding to thepixels belonging to the covered background area in frame #n consist ofonly background components, and the pixel values thereof do not change.Accordingly, the absolute value of the difference between the pixelvalues is almost 0. Thus, the stationary/moving determination made forthe pixels in frame #n−1 and frame #n−2 corresponding to the pixelsbelonging to the mixed area in frame #n by the stationary/movingdetermining portion 202-4 is “stationary”.

Since the pixels belonging to the covered background area in frame #ncontain foreground components, the pixel values thereof are differentfrom those of frame #n−1 consisting of only background components.Accordingly, the stationary/moving determination made for the pixelsbelonging to the mixed area in frame #n and the corresponding pixels inframe #n−1 by the stationary/moving determining portion 202-3 is“moving”.

When the stationary/moving determination result indicating “moving” issupplied from the stationary/moving determining portion 202-3, and whenthe stationary/moving determination result indicating “stationary” issupplied from the stationary/moving determining portion 202-4, asdiscussed above, the area determining portion 203-3 determines that thecorresponding pixels belong to a covered background area.

In FIG. 26, in frame #n in which the background is stationary and theamount of movement v in the foreground is 4, the pixels contained in anuncovered background area are the second through fourth pixels from theleft. Since the amount of movement v is 4, the second through fourthpixels from the left in the subsequent frame #n+1 contain onlybackground components and belong to the background area. In frame #n+2,which is subsequent to frame #n+1, the second through fourth pixels fromthe left contain only background components and belong to the backgroundarea.

Since the object corresponding to the background is stationary, thepixel value of the second pixel from the left in frame #n+2 does notchange from the pixel value of the second pixel from the left in frame#n+1. Similarly, the pixel value of the third pixel from the left inframe #n+2 does not change from the pixel value of the third pixel fromthe left in frame #n+1, and the pixel value of the fourth pixel from theleft in frame #n+2 does not change from the pixel value of the fourthpixel from the left in frame #n+1.

That is, the pixels in frame #n+1 and frame #n+2 corresponding to thepixels belonging to the uncovered background area in frame #n consist ofonly background components, and the pixel values thereof do not change.Accordingly, the absolute value of the difference between the pixelvalues is almost 0. Thus, the stationary/moving determination made forthe pixels in frame #n+1 and frame #n+2 corresponding to the pixelsbelonging to the mixed area in frame #n by the stationary/movingdetermining portion 202-1 is “stationary”.

Since the pixels belonging to the uncovered background area in frame #ncontain foreground components, the pixel values thereof are differentfrom those of frame #n+1 consisting of only background components.Accordingly, the stationary/moving determination made for the pixelsbelonging to the mixed area in frame #n and the corresponding pixels inframe #n+1 by the stationary/moving determining portion 202-2 is“moving”.

When the stationary/moving determination result indicating “moving” issupplied from the stationary/moving determining portion 202-2, and whenthe stationary/moving determination result indicating “stationary” issupplied from the stationary/moving determining portion 202-1, asdiscussed above, the area determining portion 203-1 determines that thecorresponding pixels belong to an uncovered background area.

FIG. 27 illustrates determination conditions for frame #n made by thearea specifying unit 103. When the determination result for the pixel inframe #n−2 located at the same image position as a pixel in frame #n tobe processed and for the pixel in frame #n−1 located at the sameposition as the pixel in frame #n is stationary, and when thedetermination result for the pixel in frame #n and the pixel in frame#n−1 located at the same image position as the pixel in frame #n ismoving, the area specifying unit 103 determines that the pixel in frame#n belongs to a covered background area.

When the determination result for the pixel in frame #n and the pixel inframe #n−1 located at the same image position as the pixel in frame #nis stationary, and when the determination result for the pixel in frame#n and the pixel in frame #n+1 located at the same image position as thepixel in frame #n is stationary, the area specifying unit 103 determinesthat the pixel in frame #n belongs to the stationary area.

When the determination result for the pixel in frame #n and the pixel inframe #n−1 located at the same image position as the pixel in frame #nis moving, and when the determination result for the pixel in frame #nand the pixel in frame #n+1 located at the same image position as thepixel in frame #n is moving, the area specifying unit 103 determinesthat the pixel in frame #n belongs to the moving area.

When the determination result for the pixel in frame #n and the pixel inframe #n+1 located at the same image position as the pixel in frame #nis moving, and when the determination result for the pixel in frame #n+1located at the same image position as the pixel in frame #n and thepixel in frame #n+2 located at the same image position as the pixel inframe #n is stationary, the area specifying unit 103 determines that thepixel in frame #n belongs to an uncovered background area.

FIGS. 28A through 28D illustrate examples of the area determinationresults obtained by the area specifying unit 103. In FIG. 28A, thepixels which are determined to belong to a covered background area areindicated in white. In FIG. 28B, the pixels which are determined tobelong to an uncovered background area are indicated in white.

In FIG. 28C, the pixels which are determined to belong to a moving areaare indicated in white. In FIG. 28D, the pixels which are determined tobelong to a stationary area are indicated in white.

FIG. 29 illustrates the area information indicating the mixed area, inthe form of an image, selected from the area information output from thedetermining-flag-storing frame memory 206. In FIG. 29, the pixels whichare determined to belong to the covered background area or the uncoveredbackground area, i.e., the pixels which are determined to belong to themixed area, are indicated in white. The area information indicating themixed area output from the determining-flag-storing frame memory 206designates the mixed area and the portions having a texture surroundedby the portions without a texture in the foreground area.

The area specifying processing performed by the area specifying unit 103is described below with reference to the flowchart of FIG. 30. In stepS201, the frame memory 201 obtains an image of frame #n−2 through frame#n+2 including frame #n.

In step S202, the stationary/moving determining portion 202-3 determineswhether the determination result for the pixel in frame #n−1 and thepixel in frame #n located at the same position is stationary. If it isdetermined that the determination result is stationary, the processproceeds to step S203 in which the stationary/moving determining portion202-2 determines whether the determination result for the pixel in frame#n and the pixel in frame #n+1 located at the same position isstationary.

If it is determined in step S203 that the determination result for thepixel in frame #n and the pixel in frame #n+1 located at the sameposition is stationary, the process proceeds to step S204. In step S204,the area determining portion 203-2 sets “1”, which indicates that thepixel to be processed belongs to the stationary area, in thestationary-area determining flag associated with the pixel to beprocessed. The area determining portion 203-2 supplies thestationary-area determining flag to the determining-flag-storing framememory 204, and the process proceeds to step S205.

If it is determined in step S202 that the determination result for thepixel in frame #n−1 and the pixel in frame #n located at the sameposition is moving, or if it is determined in step S203 that thedetermination result for the pixel in frame #n and the pixel in frame#n+1 located at the same position is moving, the pixel to be processeddoes not belong to a stationary area. Accordingly, the processing ofstep S204 is skipped, and the process proceeds to step S205.

In step S205, the stationary/moving determining portion 202-3 determineswhether the determination result for the pixel in frame #n−1 and thepixel in frame #n located at the same position is moving. If it isdetermined that the determination result is moving, the process proceedsto step S206 in which the stationary/moving determining portion 202-2determines whether the determination result for the pixel in frame #nand the pixel in frame #n+1 located at the same position is moving.

If it is determined in step S206 that the determination result for thepixel in frame #n and the pixel in frame #n+1 located at the sameposition is moving, the process proceeds to step S207. In step S207, thearea determining portion 203-2 sets “1”, which indicates that the pixelto be processed belongs to a moving area, in the moving-area determiningflag associated with the pixel to be processed. The area determiningarea 203-2 supplies the moving-area determining flag to thedetermining-flag-storing frame memory 204, and the process proceeds tostep S208.

If it is determined in step S205 that the determination result for thepixel in frame #n−1 and the pixel in frame #n located at the sameposition is stationary, or if it is determined in step S206 that thedetermination result for the pixel in frame #n and the pixel in frame#n+1 located at the same position is stationary, the pixel in frame #ndoes not belong to a moving area. Accordingly, the processing of stepS207 is skipped, and the process proceeds to step S208.

In step S208, the stationary/moving determining portion 202-4 determineswhether the determination result for the pixel in frame #n−2 and thepixel in frame #n−1 located at the same position is stationary. If it isdetermined that the determination result is stationary, the processproceeds to step S209 in which the stationary/moving determining portion202-3 determines whether the determination result for the pixel in frame#n−1 and the pixel in frame #n located at the same position is moving.

If it is determined in step S209 that the determination result for thepixel in frame #n−1 and the pixel in frame #n located at the sameposition is moving, the process proceeds to step S210. In step S210, thearea determining portion 203-3 sets “1”, which indicates that the pixelto be processed belongs to a covered background area, in thecovered-background-area determining flag associated with the pixel to beprocessed. The area determining portion 203-3 supplies thecovered-background-area determining flag to the determining-flag-storingframe memory 204, and the process proceeds to step S211. The areadetermining portion 203-3 supplies the covered-background-areadetermining flag to the determining-flag-storing frame memory 204, andthe process proceeds to step S211.

If it is determined in step S208 that the determination result for thepixel in frame #n−2 and the pixel in frame #n−1 located at the sameposition is moving, or if it is determined in step S209 that the pixelin frame #n−1 and the pixel in frame #n located at the same position isstationary, the pixel in frame #n does not belong to a coveredbackground area. Accordingly, the processing of step S210 is skipped,and the process proceeds to step S211.

In step S211, the stationary/moving determining portion 202-2 determineswhether the determination result for the pixel in frame #n and the pixelin frame #n+1 located at the same position is moving. If it isdetermined in step S211 that the determination result is moving, theprocess proceeds to step S212 in which the stationary/moving determiningportion 202-1 determines whether the determination result for the pixelin frame #n+1 and the pixel in frame #n+2 located at the same positionis stationary.

If it is determined in step S212 that the determination result for thepixel in frame #n+1 and the pixel in frame #n+2 located at the sameposition is stationary, the process proceeds to step S213. In step S213,the area determining portion 203-1 sets “1”, which indicates that thepixel to be processed belongs to an uncovered background area, in theuncovered-background-area determining flag associated with the pixel tobe processed. The area determining portion 203-1 supplies theuncovered-background-flag determining flag to thedetermining-flag-storing frame memory 204, and the process proceeds tostep S214.

If it is determined in step S211 that the determination result for thepixel in frame #n and the pixel in frame #n+1 located at the sameposition is stationary, or if it is determined in step S212 that thedetermination result for the pixel in frame #n+1 and the pixel in frame#n+2 is moving, the pixel in frame #n does not belong to an uncoveredbackground area. Accordingly, the processing of step S213 is skipped,and the process proceeds to step S214.

In step S214, the area specifying unit 103 determines whether the areasof all the pixels in frame #n are specified. If it is determined thatthe areas of all the pixels in frame #n are not yet specified, theprocess returns to step S202, and the area specifying processing isrepeated for the remaining pixels.

If it is determined in step S214 that the areas of all the pixels inframe #n are specified, the process proceeds to step S215. In step S215,the synthesizer 215 generates area information indicating the mixed areabased on the uncovered-background-area determining flag and thecovered-background-area determining flag stored in thedetermining-flag-storing frame memory 204, and also generates areainformation indicating to which of the uncovered background area, thestationary area, the moving area, or the covered background area eachpixel belongs, and sets the generated area information in thedetermining-flag-storing frame memory 206. The processing is thencompleted.

As discussed above, the area specifying unit 103 is capable ofgenerating area information indicating to which of the moving area, thestationary area, the uncovered background area, or the coveredbackground area each of the pixels contained in a frame belongs.

The area specifying unit 103 may apply logical OR to the areainformation corresponding to the uncovered background area and the areainformation corresponding to the covered background area so as togenerate area information corresponding to the mixed area, and then maygenerate area information consisting of flags indicating to which of themoving area, the stationary area, or the mixed area the individualpixels contained in the frame belong.

When the object corresponding to the foreground has a texture, the areaspecifying unit 103 is able to specify the moving area more precisely.

The area specifying unit 103 is able to output the area informationindicating the moving area as the area information indicating theforeground area, and outputs the area information indicating thestationary area as the area information indicating the background area.

The embodiment has been described, assuming that the objectcorresponding to the background is stationary. However, theabove-described area specifying processing can be applied even if theimage corresponding to the background area contains motion. For example,if the image corresponding to the background area is uniformly moving,the area specifying unit 103 shifts the overall image in accordance withthis motion, and performs processing in a manner similar to the case inwhich the object corresponding to the background is stationary. If theimage corresponding to the background area contains locally differentmotions, the area specifying unit 103 selects the pixels correspondingto the motions, and executes the above-described processing.

FIG. 31 is a block diagram illustrating the configuration of the areaspecifying unit 103. The area specifying unit 103 shown in FIG. 31 doesnot use a motion vector. A background image generator 301 generates abackground image corresponding to an input image, and supplies thegenerated background image to a binary-object-image extracting portion302. The background image generator 301 extracts, for example, an imageobject corresponding to a background object contained in the inputimage, and generates the background image.

An example of a model obtained by expanding in the time direction thepixel values of pixels aligned side-by-side in the moving direction ofan image corresponding to a foreground object is shown in FIG. 32. Forexample, if the moving direction of the image corresponding to theforeground object is horizontal with respect to the screen, the modelshown in FIG. 32 is a model obtained by expanding the pixel values ofpixels disposed side-by-side on a single line in the time domain.

In FIG. 32, the line in frame #n is the same as the line in frame #n−1and the line in frame #n+1.

In frame #n, the foreground components corresponding to the objectcontained in the sixth through seventeenth pixels from the left arecontained in the second through thirteenth pixels from the left in frame#n−1 and are also contained in the tenth through twenty-first pixel fromthe left in frame #n+1.

In frame #n−1, the pixels belonging to the covered background area arethe eleventh through thirteenth pixels from the left, and the pixelsbelonging to the uncovered background area are the second through fourthpixels from the left. In frame #n, the pixels belonging to the coveredbackground area are the fifteenth through seventeenth pixels from theleft, and the pixels belonging to the uncovered background area are thesixth through eighth pixels from the left. In frame #n+1, the pixelsbelonging to the covered background area are the nineteenth throughtwenty-first pixels from the left, and the pixels belonging to theuncovered background area are the tenth through twelfth pixels from theleft.

In frame #n−1, the pixels belonging to the background area are the firstpixel from the left, and the fourteenth through twenty-first pixels fromthe left. In frame #n, the pixels belonging to the background area arethe first through fifth pixels from the left, and the eighteenth throughtwenty-first pixels from the left. In frame #n+1, the pixels-belongingto the background area are the first through ninth pixels from the left.

An example of the background image corresponding to the example shown inFIG. 32 generated by the background image generator 301 is shown in FIG.33. The background image consists of the pixels corresponding to thebackground object, and does not contain image components correspondingto the foreground object.

The binary-object-image extracting portion 302 generates a binary objectimage based on the correlation between the background image and theinput image, and supplies the generated binary object image to a timechange detector 303.

FIG. 34 is a block diagram illustrating the configuration of thebinary-object-image extracting portion 302. A correlation-valuecalculator 321 calculates the correlation between the background imagesupplied from the background image generator 301 and the input image soas to generate a correlation value, and supplies the generatedcorrelation value to a threshold-value processor 322.

The correlation-value calculator 321 applies equation (4) to, forexample, 3×3-background image blocks having X₄ at the center, as shownin FIG. 35A, and to, for example, 3×3-background image blocks having Y₄at the center which corresponds to the background image blocks, as shownin FIG. 35B, thereby calculating a correlation value corresponding toY₄. $\begin{matrix}{{{Correlation}\quad{value}} = \frac{\underset{i = 0}{\overset{8}{\sum\quad}}{( {{Xi} - \overset{\_}{X}} ){\sum\limits_{i = 0}^{8}( {{Yi} - \overset{\_}{Y}} )}}}{\sqrt{\underset{i = 0}{\overset{8}{\sum\quad}}{( {{Xi} - \overset{\_}{X}} )^{2} \cdot {\underset{i = 0}{\overset{8}{\sum\quad}}( {{Yi} - \overset{\_}{Y}} )^{2}}}}}} & (4) \\{\overset{\_}{X} = \frac{\sum\limits_{i = 0}^{8}{Xi}}{9}} & (5) \\{\overset{\_}{Y} = \frac{\sum\limits_{i = 0}^{8}{Yi}}{9}} & (6)\end{matrix}$

The correlation-value calculator 321 supplies the correlation valuecalculated for each pixel as discussed above to the threshold-valueprocessor 322.

Alternatively, the correlation-value calculator 321 may apply equation(7) to, for example, 3×3-background image blocks having X₄ at thecenter, as shown in FIG. 36A, and to, for example, 3×3-background imageblocks having Y₄ at the center which corresponds to the background imageblocks, as shown in FIG. 36B, thereby calculating the sum of absolutevalues of differences corresponding to Y₄. $\begin{matrix}{{{Sum}\quad{of}\quad{absolute}\quad{values}\quad{of}\quad{differences}} = {\sum\limits_{i = 0}^{8}{( {{Xi} - {Yi}} )}}} & (7)\end{matrix}$

The correlation-value calculator 321 supplies the sum of the absolutevalues of the differences calculated as described above to thethreshold-value processor 322 as the correlation value.

The threshold-value processor 322 compares the pixel value of thecorrelation image with a threshold value th0. If the correlation valueis smaller than or equal to the threshold value th0, 1 is set in thepixel value of the binary object image. If the correlation value isgreater than the threshold value th0, 0 is set in the pixel value of thebinary object image. The threshold-value processor 322 then outputs thebinary object image whose pixel value is set to 0 or 1. Thethreshold-value processor 322 may store the threshold value th0 thereinin advance, or may use the threshold value th0 input from an externalsource.

FIG. 37 illustrates the binary object image corresponding to the modelof the input image shown in FIG. 32. In the binary object image, 0 isset in the pixel values of the pixels having a higher correlation withthe background image.

FIG. 38 is a block diagram illustrating the configuration of the timechange detector 303. When determining the area of a pixel in frame #n, aframe memory 341 stores a binary object image of frame #n−1, frame #n,and frame #n+1 supplied from the binary-object-image extracting portion302.

An area determining portion 342 determines the area of each pixel offrame #n based on the binary object image of frame #n−1, frame #n, andframe #n+1 so as to generate area information, and outputs the generatedarea information.

FIG. 39 illustrates the determinations made by the area determiningportion 342. When the designated pixel of the binary object image inframe #n is 0, the area determining portion 342 determines that thedesignated pixel in frame #n belongs to the background area.

When the designated pixel of the binary object image in frame #n is 1,and when the corresponding pixel of the binary object image in frame#n−1 is 1, and when the corresponding pixel of the binary object imagein frame #n+1 is 1, the area determining portion 342 determines that thedesignated pixel in frame #n belongs to the foreground area.

When the designated pixel of the binary object image in frame #n is 1,and when the corresponding pixel of the binary object image in frame#n−1 is 0, the area determining portion 342 determines that thedesignated pixel in frame #n belongs to a covered background area.

When the designated pixel of the binary object image in frame #n is 1,and when the corresponding pixel of the binary object image in frame#n+1 is 0, the area determining portion 342 determines that thedesignated pixel in frame #n belongs to an uncovered background area.

FIG. 40 illustrates an example of the determinations made by the timechange detector 303 on the binary object image corresponding to themodel of the input image shown in FIG. 32. The time change detector 303determines that the first through fifth pixels from the left in frame #nbelong to the background area since the corresponding pixels of thebinary object image in frame #n are 0.

The time change detector 303 determines that the sixth through ninthpixels from the left belong to the uncovered background area since thepixels of the binary object image in frame #n are 1, and thecorresponding pixels in frame #n+1 are 0.

The time change detector 303 determines that the tenth throughthirteenth pixels from the left belong to the foreground area since thepixels of the binary object image in frame #n are 1, the correspondingpixels in frame #n−1 are 1, and the corresponding pixels in frame #n+1are 1.

The time change detector 303 determines that the fourteenth throughseventeenth pixels from the left belong to the covered background areasince the pixels of the binary object image in frame #n are 1, and thecorresponding pixels in frame #n−1 are 0.

The time change detector 303 determines that the eighteenth throughtwenty-first pixels from the left belong to the background area sincethe corresponding pixels of the binary object image in frame #n are 0.

The area specifying processing performed by the area specifying unit 103is described below with reference to the flowchart of FIG. 41. In stepS301, the background image generator 301 of the area specifying unit 103extracts, for example, an image object corresponding to a backgroundobject contained in an input image based on the input image so as togenerate a background image, and supplies the generated background imageto the binary-object-image extracting portion 302.

In step S302, the binary-object-image extracting portion 302 calculatesa correlation value between the input image and the background imagesupplied from the background image generator 301 according to, forexample, calculation discussed with reference to FIGS. 35A and 35B. Instep S303, the binary-object-image extracting portion 302 computes abinary object image from the correlation value and the threshold valueth0 by, for example, comparing the correlation value with the thresholdvalue th0.

In step S304, the time change detector 303 executes the area determiningprocessing, and the processing is completed.

Details of the area determining processing in step S304 are describedbelow with reference to the flowchart of FIG. 42. In step S321, the areadetermining portion 342 of the time change detector 303 determineswhether the designated pixel in frame #n stored in the frame memory 341is 0. If it is determined that the designated pixel in frame #n is 0,the process proceeds to step S322. In step S322, it is determined thatthe designated pixel in frame #n belongs to the background area, and theprocessing is completed.

If it is determined in step S321 that the designated pixel in frame #nis 1, the process proceeds to step S323. In step S323, the areadetermining portion 342 of the time change detector 303 determineswhether the designated pixel in frame #n stored in the frame memory 341is 1, and whether the corresponding pixel in frame #n−1 is 0. If it isdetermined that the designated pixel in frame #n is 1 and thecorresponding pixel in frame #n−1 is 0, the process proceeds to stepS324. In step S324, it is determined that the designated pixel in frame#n belongs to the covered background area, and the processing iscompleted.

If it is determined in step S323 that the designated pixel in frame #nis 0, or that the corresponding pixel in frame #n−1 is 1, the processproceeds to step S325. In step S325, the area determining portion 342 ofthe time change detector 303 determines whether the designated pixel inframe #n stored in the frame memory 341 is 1, and whether thecorresponding pixel in frame #n+1 is 0. If it is determined that thedesignated pixel in frame #n is 1 and the corresponding pixel in frame#n+1 is 0, the process proceeds to step S326. In step S326, it isdetermined that the designated pixel in frame #n belongs to theuncovered background area, and the processing is completed.

If it is determined in step S325 that the designated pixel in frame #nis 0, or that the corresponding pixel in frame #n+1 is 1, the processproceeds to step S327. In step S327, the area determining portion 342 ofthe time change detector 303 determines that the designated pixel inframe #n belongs to the foreground area, and the processing iscompleted.

As discussed above, the area specifying unit 103 is able to specify,based on the correlation value between the input image and thecorresponding background image, to which of the foreground area, thebackground area, the covered background area, or the uncoveredbackground area each pixel of the input image belongs, and generatesarea information corresponding to the specified result.

FIG. 43 is a block diagram illustrating another configuration of thearea specifying unit 103. The area specifying unit 103 uses a motionvector and positional information thereof supplied from the motiondetector 102. The same elements as those shown in FIG. 31 are designatedwith like reference numerals, and an explanation thereof is thusomitted.

A robust-processing portion 361 generates a robust binary object imagebased on binary object images of N frames supplied from thebinary-object-image extracting portion 302, and outputs the robustbinary object image to the time change detector 303.

FIG. 44 is a block diagram illustrating the configuration of therobust-processing portion 361. A motion compensator 381 compensates forthe motion of the binary object images of N frames based on the motionvector and the positional information thereof supplied from the motiondetector 102, and outputs a motion-compensated binary object image to aswitch 382.

The motion compensation performed by the motion compensator 381 isdiscussed below with reference to examples shown in FIGS. 45 and 46. Itis now assumed, for example, that the area in frame #n is to beprocessed. When binary object images of frame #n−1, frame #n, and frame#n+1 shown in FIG. 45 are input, the motion compensator 381 compensatesfor the motion of the binary object image of frame #n−1 and the binaryobject image of frame #n+1, as indicated by the example shown in FIG.46, based on the motion vector supplied from the motion detector 102,and supplies the motion-compensated binary object images to the switch382.

The switch 382 outputs the motion-compensated binary object image of thefirst frame to a frame memory 383-1, and outputs the motion-compensatedbinary object image of the second frame to a frame memory 383-2.Similarly, the switch 382 outputs the motion-compensated binary objectimages of the third through (N-1)-th frame to frame memories 383-3through 383-(N-1), and outputs the motion-compensated binary objectimage of the N-th frame to a frame memory 383-N.

The frame memory 383-1 stores the motion-compensated binary object imageof the first frame, and outputs the stored binary object image to aweighting portion 384-1. The frame memory 383-2 stores themotion-compensated binary object image of the second frame, and outputsthe stored binary object image to a weighting portion 384-2.

Similarly, the frame memories 383-3 through 383-(N-1) stores themotion-compensated binary object images of the third through (N-1)-thframes, and outputs the stored binary object images to weightingportions 384-3 through 384-(N-1). The frame memory 383-N stores themotion-compensated binary object image of the N-th frame, and outputsthe stored binary object image to a weighting portion 384-N.

The weighting portion 384-1 multiplies the pixel value of themotion-compensated binary object image of the first frame supplied fromthe frame memory 383-1 by a redetermined weight w1, and supplies aweighted binary object image to an accumulator 385. The weightingportion 384-2 multiplies the pixel value of the motion-compensatedbinary object image of the second frame supplied from the frame memory383-2 by a predetermined weight w2, and supplies the weighted binaryobject image to the accumulator 385.

Likewise, the weighting portions 384-3 through 384-(N-1) multiply thepixel values of the motion-compensated binary object images of the thirdthrough (N-1)-th frames supplied from the frame memories 383-3 through383-(N-1) by predetermined weights w3 through w(N-1), and supplies theweighted binary object images to the accumulator 385. The weightingportion 384-N multiplies the pixel value of the motion-compensatedbinary object image of the N-th frame supplied from the frame memory383-N by a predetermined weight wN, and supplies the weighted binaryobject image to the accumulator 385.

The accumulator 385 accumulates the pixel values of themotion-compensated binary object images multiplied by the weights w1through wN of the first through N-th frames, and compares theaccumulated pixel value with the predetermined threshold value th0,thereby generating the binary object image.

As discussed above, the robust-processing portion 361 generates a robustbinary object image from N binary object images, and supplies it to thetime change detector 303. Accordingly, the area specifying unit 103configured as shown in FIG. 43 is able to specify the area moreprecisely than that shown in FIG. 31 even if noise is contained in theinput image.

The area specifying processing performed by the area specifying unit 103configured as shown in FIG. 43 is described below with reference to theflowchart of FIG. 47. The processings of step S341 through step S343 aresimilar to those of step S301 through step S303 discussed with referenceto the flowchart of FIG. 41, and an explanation thereof is thus omitted.

In step S344, the robust-processing portion 361 performs the robustprocessing.

In step S345, the time change detector 303 performs the area determiningprocessing, and the processing is completed. Details of the processingof step S345 are similar to the processing discussed with reference tothe flowchart of FIG. 42, and an explanation thereof is thus omitted.

Details of the robust processing corresponding to the processing of stepS344 in FIG. 47 are given below with reference to the flowchart of FIG.48. In step S361, the motion compensator 381 performs the motioncompensation of an input binary object image based on the motion vectorand the positional information thereof supplied from the motion detector102. In step S362, one of the frame memories 383-1 through 383-N storesthe corresponding motion-compensated binary object image supplied viathe switch 382.

In step S363, the robust-processing portion 361 determines whether Nbinary object images are stored. If it is determined that N binaryobject images are not stored, the process returns to step S361, and theprocessing for compensating for the motion of the binary object imageand the processing for storing the binary object image are repeated.

If it is determined in step S363 that N binary object images are stored,the process proceeds to step S364 in which weighting is performed. Instep S364, the weighting portions 384-1 through 384-N multiply thecorresponding N binary object images by the weights w1 through wN.

In step S365, the accumulator 385 accumulates the N weighted binaryobject images.

In step S366, the accumulator 385 generates a binary object image fromthe accumulated images by, for example, comparing the accumulated valuewith a predetermined threshold value th1, and the processing iscompleted.

As discussed above, the area specifying unit 103 configured as shown inFIG. 43 is able to generate area information based on the robust binaryobject image.

As is seen from the foregoing description, the area specifying unit 103is able to generate area information indicating to which of the movingarea, the stationary area, the uncovered background area, or the coveredbackground area each pixel contained in a frame belongs.

FIG. 49 is a block diagram illustrating the configuration of themixture-ratio calculator 104. An estimated-mixture-ratio processor 401calculates an estimated mixture ratio for each pixel by calculating amodel of a covered background area based on the input image, andsupplies the calculated estimated mixture ratio to a mixture-ratiodetermining portion 403.

An estimated-mixture-ratio processor 402 calculates an estimated mixtureratio for each pixel by calculating a model of an uncovered backgroundarea based on the input image, and supplies the calculated estimatedmixture ratio to the mixture-ratio determining portion 403.

Since it can be assumed that the object corresponding to the foregroundis moving with constant velocity within the shutter time, the mixtureratio α of the pixels belonging to a mixed area exhibits the followingcharacteristics. That is, the mixture ratio α linearly changes accordingto the positional change in the pixels. If the positional change in thepixels is one-dimensional, a change in the mixture ratio α can berepresented linearly. If the positional change in the pixels istwo-dimensional, a change in the mixture ratio α can be represented on aplane.

Since the period of one frame is short, it can be assumed that theobject corresponding to the foreground is a rigid body moving withconstant velocity.

The gradient of the mixture ratio α is inversely proportional to theamount of movement v within the shutter time of the foreground.

An example of the ideal mixture ratio α is shown in FIG. 50. Thegradient 1 of the ideal mixture ratio α in the mixed area can berepresented by the reciprocal of the amount of movement v.

As shown in FIG. 50, the ideal mixture ratio α has the value of 1 in thebackground area, the value of 0 in the foreground area, and the value ofgreater than 0 and smaller than 1 in the mixed area.

In the example shown in FIG. 51, the pixel value C06 of the seventhpixel from the left in frame #n can be indicated by equation (8) byusing the pixel value P06 of the seventh pixel from the left in frame#n−1. $\begin{matrix}\begin{matrix}{{C06} = {{{B06}/v} + {{B06}/v} + {{F01}/v} + {{F02}/v}}} \\{= {{{P06}/v} + {{P06}/v} + {{F01}/v} + {{F02}/v}}} \\{= {{{2/v} \cdot {P06}} + {\sum\limits_{i = 1}^{2}{{Fi}/v}}}}\end{matrix} & (8)\end{matrix}$

In equation (8), the pixel value C06 is indicated by a pixel value M ofthe pixel in the mixed area, while the pixel value P06 is indicated by apixel value B of the pixel in the background area. That is, the pixelvalue M of the pixel in the mixed area and the pixel value B of thepixel in the background area can be represented by equations (9) and(10), respectively.M=C06   (9)B=P06   (10)

In equation (8), 2/v corresponds to the mixture ratio α. Since theamount of movement v is 4, the mixture ratio α of the seventh pixel fromthe left in frame #n is 0.5.

As discussed above, the pixel value C in the designated frame #n isconsidered as the pixel value in the mixed area, while the pixel value Pof frame #n−1 prior to frame #n is considered as the pixel value in thebackground area. Accordingly, equation (3) indicating the mixture ratioα can be represented by equation (11):C=α·P+f   (11)where f in equation (11) indicates the sum of the foreground componentsΣ_(i)Fi/v contained in the designated pixel. The variables contained inequation (11) are two factors, i.e., the mixture ratio α and the sum fof the foreground components.

Similarly, a model obtained by expanding in the time direction the pixelvalues in which the amount of movement is 4 and the number of virtualdivided portions is 4 in an uncovered background area is shown in FIG.52.

As in the representation of the covered background area, in theuncovered background area, the pixel value C of the designated frame #nis considered as the pixel value in the mixed area, while the pixelvalue N of frame #n+1 subsequent to frame #n is considered as thebackground area. Accordingly, equation (3) indicating the mixture ratioα can be represented by equation (12).C=α·N+f   (12)

The embodiment has been described, assuming that the background objectis stationary. However, equations (8) through (12) can be applied to thecase in which the background object is moving by using the pixel valueof a pixel located corresponding to the amount of movement v of thebackground. It is now assumed, for example, in FIG. 51 that the amountof movement v of the object corresponding to the background is 2, andthe number of virtual divided portions is 2. In this case, when theobject corresponding to the background is moving to the right in FIG.49, the pixel value B of the pixel in the background area in equation(10) is represented by a pixel value P04.

Since equations (11) and (12) each contain two variables, the mixtureratio α cannot be determined without modifying the equations.

The mixture ratio α linearly changes in accordance with a change in theposition of the pixels because the object corresponding to theforeground is moving with constant velocity. By utilizing thischaracteristic, an equation in which the mixture ratio α and the sum fof the foreground components are approximated in the spatial directioncan hold true. By utilizing a plurality of sets of the pixel values ofthe pixels belonging to the mixed area and the pixel values of thepixels belonging to the background area, the equations in which themixture ratio α and the sum f of the foreground components areapproximated are solved by assuming that the mixture ratio α linearlychanges and that the sum of the foreground components linearly changes,as shown in FIG. 53.

As shown in FIG. 53, the data that can be utilized for calculating themixture ratio α of the pixels belonging to the covered background areaincludes the pixel values M01 through M05, which contain the pixel valueof a designated pixel of the designated frame #n, and the pixel valuesP01 through P05 of frame #n−1.

The mixture ratio α differs according to the spatial position, and isrepresented by α01 through α05.

The sum of the foreground components differs according to the spatialposition, and is represented by f01 through f05.

When the mixture ratio α is approximated in the plane, the mixture ratioα can be represented by equation (13) by considering the movement vcorresponding to the two directions, i.e., the horizontal direction andthe vertical direction of the image.αx=jm+kq+p   (13)In equation (13), x indicates one of 01 through 05. In equation (13), jis the index in the horizontal direction, and k is the index in thevertical direction when the position of the designated pixel is 0. Inequation (13), m designates the horizontal gradient of the mixture ratioα in the plane, and q indicates the vertical gradient of the mixtureratio α in the plane. In equation (13), p indicates the intercept of themixture ratio α in the plane.

The sum of the foreground components can be expressed by equation (14).fx=js+kt+u   (14)

In equation (14), x indicates one of 01 through 05. In equation (14), jis the index in the horizontal direction, and k is the index in thevertical direction when the position of the designated pixel is 0. Inequation (14), s designates the horizontal gradient of the sum of theforeground components in the plane, and t indicates the verticalgradient of the sum of the foreground components in the plane. Inequation (14), u indicates the intercept of the sum of the foregroundcomponents in the plane.

For example, by applying 5×5-pixel values that are spatially located inclose proximity with each other to the equations containing the sixvariables, m, q, p, s, t, and u, 25 equations can be obtained for thesix variables. By solving the obtained equations with the method ofleast squares, the six variables can be determined.

When the object corresponding to the foreground is moving fast in theshutter time, the mixture ratio α of the pixels that are spatiallylocated in close proximity with each other is uniform, and the sum ofthe foreground components of the pixels that are spatially located inclose proximity with each other is uniform due to the spatialcorrelation of the foreground object. By utilizing this assumption,equations in which the mixture ratio α and the sum f of the foregroundcomponents are approximated in the spatial direction can hold true.

More specifically, concerning the first term of the right side ofequation (3), the mixture ratio approximates to be uniform, as indicatedby equation (15), which is described below, and also, concerning thesecond term of the right side of equation (3), the sum of the foregroundcomponents approximates to be uniform, as indicated by equation (21),which is described below.

By utilizing a plurality of sets of the pixel values of the pixelsbelonging to the mixed area and the pixel values of the pixels belongingto the background area, the equation in which the mixture ratio α andthe sum f of the foreground components are approximated is solved.

By approximating the mixture ratio α assuming that the mixture ratio αin the pixels which are spatially in close proximity with each other isuniform, the mixture ratio α can be expressed by equation (15).α=n   (15)

As shown in FIG. 54, i indicates the spatial index when the position ofthe designated pixel is set to 0. In FIG. 54, the white dot indicatesthe designated pixel, and the black dots indicate the pixels located inclose proximity with the designated pixel. In equation (15), n is theapproximated value of the mixture ratio α and is also the mixture ratioα of the designated pixel corresponding to the index, which is 0.

Although the index i is known, n is unknown.

By approximating the mixture ratio α, as indicated by equation (15), aplurality of different mixture ratios α for a plurality of pixels can beexpressed by one variable. In the example shown in FIG. 54, the fivemixture ratios α for the five pixels can be expressed by one variable,i.e., n.

By approximating the mixture ratio α in the plane shown in FIG. 55,equation (15) is expanded into the plane, and the mixture ratio α can beexpressed by equation (16).α=n   (16)

In FIG. 55, i indicates the horizontal index when the position of thedesignated pixel is set to 0, and j indicates the vertical index whenthe position of the designated pixel is set to 0. In FIG. 55, the whitedot indicates the designated pixel.

As shown in FIG. 56, the data that can be utilized for calculating themixture ratio α of the pixels belonging to the covered background areaincludes the pixel values M01 through M05, which contain the pixel valueof the designated pixel of the designated frame #n, and the pixel valuesP01 through P05 of frame #n−1.

Since the mixture ratio α approximates to be uniform regardless of thespatial position, it is represented by the mixture ratio α.

Since the sum of the foreground components approximates to be uniformregardless of the spatial position, it is represented by f.

For example, in frame #n shown in FIG. 51, equations (17) through (19)can hold true for C05 through C07.C 05=α05·B 05/v+f 05   (17)C 06=α06·B 06/v+f 06   (18)C 07=α07·B 07/v+f 07   (19)

Assuming that the foreground components of the pixels positioned inclose proximity with each other are equal, i.e., that F01 through F03are equal, equation (20) holds true by replacing F01 through F03 by fc.fx=Fc   (20)In equation (20), x indicates the position in the spatial direction.

When i indicates the horizontal index, and j indicates the verticalindex, equation (20) can be expressed by equation (21).fi, j=u   (21)

In equation (21), u is indicated by Fc, as expressed by equation (22).u=Fc

That is, the approximation in which the sum of the foreground componentsof the pixels located in close proximity with each other is uniform canbe expressed by equation (21).

Assuming that the mixture ratio α of the pixels located in closeproximity with each other approximates to be uniform, and that the sumof the foreground components of the pixels located in close proximitywith each other approximates to be uniform, equations (15) and (21) aresubstituted into equation (3), thereby obtaining equation (23).M=n·B+u   (23)Equation (23) contains two variables, i.e., n and u.

For determining the mixture ratio α, the number of equations isincreased by setting the pixel values of the pixels spatially located inthe close proximity with each other in equation (23) while maintainingthe two variables. More specifically, according to the pixels in closeproximity with the designated pixel, the pixel value M or the pixelvalue B is set in the normal equation corresponding to equation (23).Then, a plurality of normal equations in which the pixel value M or thepixel value B is set are solved by the method of least squares, therebycalculating the mixture ratio α.

For example, the horizontal index i of the designated pixel is set to 0,and the vertical index j is set to 0. Then, the pixel value M or thepixel value B is set in equation (23) for 3×3 pixels located close tothe designated pixel, thereby obtaining equations (24) through (32).M _(−1,−1) =B _(−1,−1) ·n+u   (24)M _(0,−1) =B _(0,−1) ·n+u   (25)M _(+1,−1) =B _(+1,−1) ·n+u   (26)M _(−1,0) =B _(−1,0) ·n+u   (27)M _(0,0) =B _(0,0) ˜n+u   (28)M _(+1,0) =B _(+1,0) ·n+u   (29)M _(−1,+1) =B _(−1,+1) ·n+u   (30)M _(0,+1) =B _(0,+1) ·n+u   (31)M _(+1,+1) =B _(+1,+1) ·n+u   (32)

Nine equations (24) through (32) are obtained for the two variables uand n, and are solved by the method of least squares, therebydetermining the two variables u and n. In this case, the mixture ratioax of the designated pixel corresponds to the variable n in equation(23). Accordingly, between the two determined variables u and n, thevariable h is output as the mixture ratio α.

A description has been given with reference to equations (24) through(32), by assuming that the pixel value of the pixel contained in themixed area is M, and the pixel value of the pixel contained in thebackground area is B. In this case, it is necessary to set normalequations for each of the cases where the designated pixel is containedin the covered background area, or the designated pixel is contained inthe uncovered background area.

For example, when the mixture ratio α of the pixel contained in thecovered background area in frame #n shown in FIG. 51 is determined, C04through C08 of the pixels in frame #n and the pixel values P04 throughP08 of the pixels in frame #n−1 are set in the normal equations.

For determining the mixture ratio α of the pixel contained in theuncovered background area in frame #n shown in FIG. 52, the pixels C28through C32 of frame #n and the pixel values N28 through N32 of thepixels in frame #n+1 are set in the normal equations.

When the model corresponding to the covered background area is used, itis set that M=C and B=P in equations (24) through (32). In contrast,when the model corresponding to the uncovered background area is used,it is set that M=C and B=N in equations (24) through (32).

More specifically, for example, for calculating the mixture ratio α ofthe pixel contained in the covered background area shown in FIG. 57, thefollowing equations (33) through (41) are established. The pixel valueof the pixel whose mixture ratio α is to be calculated is Mc5. In FIG.57, the white dots indicate pixels to be considered as the background,and the black dots indicate pixels to be considered as the mixed area.Mc 1=Bc 1·n+u   (33)Mc 2=Bc 2·n+u   (34)Mc 3=Bc 3·n+u   (35)Mc 4=Bc 4·n+u   (36)Mc 5=Bc 5·n+u   (37)Mc 6=Bc 6·n+u   (38)Mc 7=Bc 7·n+u   (39)Mc 8=Bc 8·n+u   (40)Mc 9=Bc 9·n+u   (41)

When calculating the mixture ratio α of the pixel contained in thecovered background area in frame #n, the pixel values Bc1 through Bc9 ofthe pixels in the background area in frame #n−1 corresponding to thepixels in frame #n are used in equations (33) through (41). Since nineequations (33) through (41) are established for the two variables u andn, they can be solved by the method of least squares.

When calculating the mixture ratio α of the pixel contained in theuncovered background area shown in FIG. 57, the following equations (42)through (50) can hold true. The pixel value of the pixel whose mixtureratio α is to be calculated is Mu5.Mu 1=Bu 1·n+u   (42)Mu 2=Bu 2·n+u   (43)Mu 3=Bu 3·n+u   (44)Mu 4=Bu 4·n+u   (45)Mu 5=Bu 5·n+u   (46)Mu 6=Bu 6·n+u   (47)Mu 7=Bu 7·n+u   (48)Mu 8=Bu 8·n+u   (49)Mu 9=Bu 9·n+u   (50)

When calculating the mixture ratio α of the pixel contained in theuncovered background area in frame #n, the pixel values Bu1 through Bu9of the pixels of the background area in frame #n+1 corresponding to thepixels of frame #n are used in equations (42) through (50). Since nineequations (42) through (50) are established for the two variables u andn, they can be solved by the method of least squares.

A specific process for calculating the mixture ratio α by applying themethod of least squares is described below.

For the sake of simplicity, in equation (23), n is indicated by w0, andu is indicated by w1. Similarly, in equation (23), the value B relatingto n is indicated by a0, and the value 1 relating to u is indicated bya1.

Also, a combination of the horizontal index i and the vertical index jin equations (24) through (32) is indicated by a single index k.

When the index i and the index j are indicated by a single index k, therelationship among the index i, the index j, and the index k isexpressed by equation (51).k=(i+1)·3+(j+1)   (51)

In consideration of the error ek, equations (24) through (32) can bemodified into equation (52). $\begin{matrix}{{Mk} = {{\sum\limits_{h = 0}^{I}{{ah} \cdot {wh}}} + e_{k}}} & (52)\end{matrix}$In equation (52), k is any one of the integers from 0 to 8.

Equation (53) can be found from equation (52). $\begin{matrix}{e_{k} = {{Mk} - {\sum\limits_{h = 0}^{I}{{ah} \cdot {wh}}}}} & (53)\end{matrix}$

Since the method of least squares is applied, the square sum E of theerror is defined as follows, as expressed by equation (54).$\begin{matrix}{E = {\sum\limits_{k = 0}^{8}e_{k}^{2}}} & (54)\end{matrix}$

In order to minimize the error, the partial differential value of thevariable Wv with respect to the square sum E of the error should be 0. vis an integer either 0 or 1. Thus, wv is determined so that equation(55) is satisfied. $\begin{matrix}\begin{matrix}{\frac{\partial E}{\partial w_{v}} = {2 \cdot {\sum\limits_{x = 0}^{8}{e_{k} \cdot \frac{\partial e_{k}}{\partial w_{v}}}}}} \\{= {{2 \cdot {\sum\limits_{x = 0}^{8}{e_{k} \cdot a_{v}}}} = 0}}\end{matrix} & (55)\end{matrix}$

By substituting equation (53) into equation (55), equation (56) isobtained. $\begin{matrix}{{\sum\limits_{k = 0}^{8}( {a_{v} \cdot {\sum\limits_{h = 0}^{I}{{ah} \cdot {wh}}}} )} = {\sum\limits_{k = 0}^{8}{a_{v} \cdot {Mk}}}} & (56)\end{matrix}$

From the two equations obtained by substituting one of the integers 0and 1 into v in equation (56), wh (h=0,1) is determined.

As discussed above, the determined result w0, i.e., n, is set in themixture ratio α corresponding to the designated pixel.

In this manner, the mixture-ratio calculator 104 is able to determinethe mixture ratio α with a relatively simple calculation, by assumingthat the mixture ratio α of the pixels in close proximity with eachother approximates to be uniform and that the sum of the foregroundcomponents of the pixels in close proximity with each other approximatesto be uniform.

When the foreground object is moving fast in the shutter time, it can beassumed that the mixture ratio α of the pixels spatially located inclose proximity with each other is uniform, and that the sum of theforeground components of the pixels spatially located in close proximitywith each other linearly changes due to the spatial correlation of theforeground object. Based on these assumptions, equations in which themixture ratio a and the sum f of the foreground components areapproximated can be established.

As shown in FIG. 58, the data that can be utilized for calculating themixture ratio α of the pixels belonging to the covered background areaincludes the pixel values M01 through M05, which contain the pixel valueof the designated pixel of the designated frame #n, and the pixel valuesP01 through P05 of frame #n−1.

The mixture ratio α approximates to be uniform regardless of the spatialposition, and is thus represented by the mixture ratio α.

The sum of the foreground components is different according to thespatial position, and is thus represented by f01 through f05.

The mixture ratio α in which α approximates to be uniform is expressedby equation (57).α=p   (57)

f01 through f05 approximating to be linear is expressed by equation(58).fx=js+kt+u   (58)In equation (58), x is one of 01 through 05.

With this arrangement, for example, by applying the pixel values of 5×5pixels spatially located in close proximity with each other to theequations containing the four variables, i.e., p, s, t, and u, 25equations can be obtained for the four variables. The obtained equationsare solved by the method of least squares, thereby determining the fourvariables.

For example, it is now assumed that the mixture ratio of the 5×5 pixelsspatially located in close proximity with each other is uniform, andthat the sum of the foreground components of the pixels spatiallylocated in close proximity with each other linearly changes. Then, thepixel values spatially located in close proximity with each other areset in the equations by applying four variables, that is, one variableindicating the mixture ratio and three variables indicating the gradientand the intercepts, and the equations in which the pixel values are setare solved by the method of least squares.

This is described below by taking an example in which 3×3 pixels inclose proximity with the designated pixel are processed.

When the horizontal index and the vertical index for the designatedpixel are indicated by i and j (the designated pixel is 0), nineequations are established for 3×3 pixels as expressed by equations (59)through (67).M _(−1,−1) =B _(−1,−1) ·n+(−1)·s+(−1)·t+u   (59)M _(0,−1) =B _(0,−1) ·n+0·s+(−1)·t+u   (60)M _(+1,−1) =B _(+1,−1) ·n+(−1)·s+(−1)·t+u   (61)M _(−1,0) =B _(−1,0) ·n+(−1)·s+0·t+u   (62)M _(0,0) =B _(0,0) ·n+0·s+0·t+u   (63)M _(+1,0) =B _(+1,0) ·n+(+1)·s+0·t+u   (64)M _(−1,+1) =B _(−1,+1) ·n+(−1)·s+(+1)·t+u   (65)M _(0,+1) =B _(0,+1) ·n+0·s+(+1)·t+u   (66)M _(+1,+1) =B _(+1,+1) ·n+(+1)·s+(+1)·t+u   (67)

Nine equations (59) through (67) are obtained for the four variables u,s, t, and n, and are solved by the method of least squares, therebydetermining the four variables u, s, t, and n. In this case, the mixtureratio α of the designated pixel corresponds to n in equation (23).Accordingly, among the four determined variables, n is output as themixture ratio α.

A description has been given with reference to equations (59) through(67), by assuming that the pixel value of the pixel contained in themixed area is M, and the pixel value of the pixel contained in thebackground area is B. In this case, it is necessary to set normalequations for each of the cases where the designated pixel is containedin the covered background area, or the designated pixel is contained inthe uncovered background area.

For example, when the mixture ratio α of the pixel contained in thecovered background area in frame #n shown in FIG. 51 is determined, C04through C08 of the pixels in frame #n and the pixel values P04 throughP08 of the pixels in frame #n−1 are set in the normal equations.

For determining the mixture ratio α of the pixel contained in theuncovered background area in frame #n shown in FIG. 52, the pixels C28through C32 of frame #n and the pixel values N28 through N32 of thepixels in frame #n+1 are set in the normal equations.

When the model corresponding to the covered background area is used, itis set that M=C and B=P in equations (59) through (67). In contrast,when the model corresponding to the uncovered background area is used,it is set that M=C and B=N in equations (59) through (67).

More specifically, for example, for calculating the mixture ratio α ofthe pixel contained in the covered background area shown in FIG. 57, thefollowing equations (68) through (76) are established. The pixel valueof the pixel whose mixture ratio α is to be calculated is Mc5.Mc 1=Bc 1·n+(−1)+s+(−1)·t+u   (68)Mc 2=Bc 2·n+0+s+(−1)·t+u   (69)Mc 3=Bc 3·n+(+1)+s+(−1)·t+u   (70)Mc 4=Bc 4·n+(−1)+s+0·t+u   (71)Mc 5=Bc 5·n+0+s+0·t+u   (72)Mc 6=Bc 6·n+(+1)+s+0·t+u   (73)Mc 7=Bc 7·n+(−1)+s+(+1)·t+u   (74)Mc 8=Bc 8·n+0+s+(+1)·t+u   (75)Mc 9=Bc 9·n+(+1)+s+(+1)·t+u   (76)

When calculating the mixture ratio α of the pixel contained in thecovered background area in frame #n, the pixel values Bc1 through Bc9 ofthe pixels in the background area in frame #n−1 corresponding to thepixels in frame #n are used in equations (68) through (76). Since nineequations (68) through (76) are established for the four variables, theycan be solved by the method of least squares.

When calculating the mixture ratio α of the pixel contained in theuncovered background area shown in FIG. 57, the following equations (77)through (85) can hold true. The pixel value of the pixel whose mixtureratio α is to be calculated is Mu5.Mu 1=Bu 1·n+(−1)·s+(−1)·t+u   (77)Mu 2=Bu 2·n+0·s+(−1)·t+u   (78)Mu 3=Bu 3·n+(+1)·s+(−1)·t+u   (79)Mu 4=Bu 4·n+(−1)·s+0·t+u   (80)Mu 5=Bu 5·n+0·s+0·t+u   (81)Mu 6=Bu 6·n+(+1)·s+0·t+u   (82)Mu 7=Bu 7·n+(−1)·s+(+1)·t+u   (83)Mu 8=Bu 8·n+0·s+(+1)·t+u   (84)Mu 9=Bu 9·n+(+1)·s+(+1)·t+u   (85)

When calculating the mixture ratio α of the pixel contained in theuncovered background area in frame #n, the pixel values Bu1 through Bu9of the pixels of the background area in frame #n+1 corresponding to thepixels of frame #n are used in equations (77) through (85). Since nineequations (77) through (85) are established for the four variables, theycan be solved by the method of least squares.

A specific process for calculating the mixture ratio α by applying themethod of least squares is described below.

For the sake of simplicity, the four variables, n, s, t, and u areindicated by w0, w1, w2, and w3, respectively. The values B, i, j, and lrelating to the four variables, n, s, t, and u are indicated by a0, a1,a2, and a3, respectively.

Also, a combination of the horizontal index i and the vertical index jin equations (59) through (67) is indicated by a single index k.

When the index i and the index j are indicated by a single index k, therelationship among the index i, the index j, and the index k isexpressed by equation (86).k=(i+1)·3+(j+1)   (86)

In consideration of the error ek, equations (59) through (67) can bemodified into equation (87). $\begin{matrix}{{Mk} = {{\sum\limits_{h = 0}^{3}{{ah} \cdot {wh}}} + e_{k}}} & (87)\end{matrix}$

In equation (87), k is any one of the integers from 0 to 8.

Equation (88) can be found from equation (87). $\begin{matrix}{e_{k} = {{Mk} - {\sum\limits_{h = 0}^{3}{{ah} \cdot {wh}}}}} & (88)\end{matrix}$

Since the method of least squares is applied, the square sum E of theerror is defined as follows, as expressed by equation (89).$\begin{matrix}{E = {\sum\limits_{k = 0}^{8}e_{k}^{2}}} & (89)\end{matrix}$

In order to minimize the error, the partial differential value of thevariable Wv with respect to the square sum E of the error should be 0. vis any one of the integers from 0 to 4. Thus, wv is determined so thatequation (90) is satisfied. $\begin{matrix}\begin{matrix}{\frac{\partial E}{\partial w_{v}} = {2 \cdot {\sum\limits_{k = 0}^{8}{e_{k} \cdot \frac{\partial e_{k}}{\partial w_{v}}}}}} \\{= {{2 \cdot {\sum\limits_{k = 0}^{8}{e_{k} \cdot a_{v}}}} = 0}}\end{matrix} & (90)\end{matrix}$

By substituting equation (88) into equation (90), equation (91) isobtained. $\begin{matrix}{{\sum\limits_{k = 0}^{8}( {a_{v} \cdot {\sum\limits_{h = 0}^{3}{{ah} \cdot {wh}}}} )} = {\sum\limits_{k = 0}^{8}{a_{v} \cdot {Mk}}}} & (91)\end{matrix}$

From the four equations obtained by substituting one of the integers 0through 4 into v in equation (91), wh (h=0, 1, 2, 3) is determined.

As discussed above, the determined result w0, i.e., n, is set in themixture ratio α corresponding to the designated pixel.

In this manner, the mixture-ratio calculator 104 is able to determinethe mixture ratio α with a relatively simple calculation and arelatively high precision, by assuming that the mixture ratio α of thepixels in close proximity with each other approximates to be uniform andthat the sum of the foreground components of the pixels in closeproximity with each other approximates to change linearly. When themixture ratio α of the pixels in close proximity with each otherapproximates to be uniform, and when the sum of the foregroundcomponents of the pixels in close proximity with each other approximatesto change linearly, with a gradation of the foreground object, themixture-ratio calculator 104 is able to determine the mixture ratio αwith higher precision compared to when the mixture ratio α of the pixelsin close proximity with each other is uniform and when the sum of theforeground components is uniform.

FIG. 59 is a block diagram illustrating the configuration of theestimated-mixture-ratio processor 401. An image input into theestimated-mixture-ratio processor 401 is supplied to a delay circuit 421and an adder 422.

The delay circuit 421 delays the input image for one frame, and suppliesthe image to the adder 422. When frame #n is supplied as the input imageto the adder 422, the delay circuit 421 supplies frame #n−1 to the adder422.

The adder 422 sets the pixel value of the pixel adjacent to the pixelfor which the mixture ratio α is calculated, and the pixel value offrame #n−1 in the normal equation. For example, the adder 422 sets thepixel values Mc1 through Mc9 and the pixel values Bc1 through Bc9 in thenormal equations based on equations (33) through (41), respectively. Theadder 422 supplies the normal equations in which the pixel values areset to a calculator 423.

The calculator 423 determines the estimated mixture ratio by solving thenormal equations supplied from the adder 422, and outputs the determinedestimated mixture ratio.

In this manner, the estimated-mixture-ratio processor 401 is able tocalculate the estimated mixture ratio based on the input image, andsupplies it to the mixture-ratio determining portion 403.

The estimated-mixture-ratio processor 402 is configured similar to theestimated-mixture-ratio processor 401, and an explanation thereof isthus omitted.

FIG. 60 is a block diagram illustrating another configuration of themixture-ratio calculator 104. The same portions as those shown in FIG.49 are indicated by like reference numerals, and an explanation thereofis thus omitted.

A selector 441 supplies a pixel belonging to the covered background areaand the corresponding pixel in the previous frame to anestimated-mixture-ratio processor 401 based on the area informationsupplied from the area specifying unit 103. The selector 441 supplies apixel belonging to the uncovered background area and the correspondingpixel in the subsequent frame to an estimated-mixture-ratio processor402 based on the area information supplied from the area specifying unit103.

Based on the area information supplied from the area specifying unit103, the selector 442 sets the mixture ratio α to 0 when the designatedpixel belongs to the foreground area, and sets the mixture ratio α to 1when the designated pixel belongs to the background area. When thedesignated pixel belongs to the covered background area, the selector442 selects the estimated mixture ratio supplied from theestimated-mixture-ratio processor 401 and sets it as the mixture ratioα. When the designated pixel belongs to the uncovered background area,the selector 442 selects the estimated mixture ratio supplied from theestimated-mixture-ratio processor 402 and sets it as the mixture ratioα. The selector 442 then outputs the mixture ratio α which has beenselected and set based on the area information.

As discussed above, the mixture-ratio calculator 104 configured as shownin FIG. 60 is able to calculate the mixture ratio α for each pixelcontained in the image, and outputs the calculated mixture ratio α.

The calculation processing for the mixture ratio α performed by themixture-ratio calculator 104 configured as shown in FIG. 49 is discussedbelow with reference to the flowchart of FIG. 61. In step S401, themixture-ratio calculator 104 obtains area information supplied from thearea specifying unit 103. In step S402, the estimated-mixture-ratioprocessor 401 executes the processing for estimating the mixture ratioby using a model corresponding to a covered background area, andsupplies the estimated mixture ratio to the mixture-ratio determiningportion 403. Details of the processing for estimating the mixture ratioare discussed below with reference to the flowchart of FIG. 62.

In step S403, the estimated-mixture-ratio processor 402 executes theprocessing for estimating the mixture ratio by using a modelcorresponding to an uncovered background area, and supplies theestimated mixture ratio to the mixture-ratio determining portion 403.

In step S404, the mixture-ratio calculator 104 determines whether themixture ratios have been estimated for the whole frame. If it isdetermined that the mixture ratios have not yet been estimated for thewhole frame, the process returns to step S402, and the processing forestimating the mixture ratio for the subsequent pixel is executed.

If it is determined in step S404 that the mixture ratios have beenestimated for the whole frame, the process proceeds to step S405. Instep S405, the mixture-ratio determining portion 403 sets the mixtureratio based on the area information supplied from the area specifyingunit 103 and indicating to which of the foreground area, the backgroundarea, the covered background area, or the uncovered background area thepixel for which the mixture ratio α is to be calculated belongs. Themixture-ratio determining portion 403 sets the mixture ratio α to 0 whenthe corresponding pixel belongs to the foreground area, and sets themixture ratio α to 1 when the corresponding pixel belongs to thebackground area. When the corresponding pixel belongs to the coveredbackground area, the mixture-ratio determining portion 403 sets theestimated mixture ratio supplied from the estimated-mixture-ratioprocessor 401 as the mixture ratio α. When the corresponding pixelbelongs to the uncovered background area, the mixture-ratio determiningportion 403 sets the estimated mixture ratio supplied from theestimated-mixture-ratio processor 402 as the mixture ratio α. Theprocessing is then completed.

As discussed above, the mixture-ratio calculator 104 is able tocalculate the mixture ratio α, which indicates a feature quantitycorresponding to each pixel, based on the area information supplied fromthe area specifying unit 103, and the input image.

The processing for calculating the mixture ratio α performed by themixture-ratio calculator 104 configured as shown in FIG. 60 is similarto that discussed with reference to the flowchart of FIG. 61, and anexplanation thereof is thus omitted.

A description is now given, with reference to the flowchart of FIG. 62,of the mixture-ratio estimating processing by theestimated-mixture-ratio processor 401 having the configuration shown inFIG. 59 by using a model of the covered background area.

In step S421, the adder 422 sets the pixel value contained in the inputimage and the pixel value contained in the image supplied from the delaycircuit 421 in a normal equation corresponding to a model of the coveredbackground area.

In step S422, the estimated-mixture-ratio processor 401 determineswhether the setting of the target pixels is finished. If it isdetermined that the setting of the target pixels is not finished, theprocess returns to step S421, and the processing for setting the pixelvalues in the normal equation is repeated.

If it is determined in step S422 that the setting for the target pixelsis finished, the process proceeds to step S423. In step S423, acalculator 423 calculates the estimated mixture ratio based on thenormal equations in which the pixels values are set, and outputs thecalculated mixture ratio.

As discussed above, the estimated-mixture-ratio processor 401 having theconfiguration shown in FIG. 59 is able to calculate the estimatedmixture ratio based on the input image.

The mixture-ratio estimating processing by using a model correspondingto the uncovered background area is similar to the processing indicatedby the flowchart of FIG. 62 by using the normal equations correspondingto a model of the uncovered background area, and an explanation thereofis thus omitted.

The embodiment has been described, assuming that the objectcorresponding to the background is stationary. However, theabove-described mixture-ratio calculation processing can be applied evenif the image corresponding to the background area contains motion. Forexample, if the image corresponding to the background area is uniformlymoving, the estimated-mixture-ratio processor 401 shifts the overallimage in accordance with this motion, and performs processing in amanner similar to the case in which the object corresponding to thebackground is stationary. If the image corresponding to the backgroundarea contains locally different motions, the estimated-mixture-ratioprocessor 401 selects the pixels corresponding to the motions as thepixels belonging to the mixed area, and executes the above-describedprocessing.

As described above, the mixture-ratio calculator 102 is able tocalculate the mixture ratio α, which is a feature quantity correspondingto each pixel, based on the input image and the area informationsupplied to the area specifying unit 101.

By utilizing the mixture ratio α, it is possible to separate theforeground components and the background components contained in thepixel values while maintaining the information of motion blur containedin the image corresponding to the moving object.

By combining the images based on the mixture ratio a, it is alsopossible to create an image which contains correct motion blur thatcoincides with the speed of a moving object and which faithfullyreflects the real world.

FIG. 63 is a block diagram illustrating another configuration of themixture-ratio calculator 104. An estimated-mixture-ratio processor 501calculates an estimated mixture ratio for each pixel by calculating amodel of a covered background area based on the input image and themotion vector and the positional information thereof supplied from themotion detector 102, and supplies the calculated estimated mixture ratioto a mixture-ratio determining portion 503.

An estimated-mixture-ratio processor 502 calculates an estimated mixtureratio for each pixel by calculating a model of an uncovered backgroundarea based on the motion vector and the positional information thereofsupplied from the motion detector 102 and the input image, and suppliesthe calculated estimated mixture ratio to the mixture-ratio determiningportion 503.

The mixture ratio α linearly changes in accordance with a change in theposition of the pixels because the object corresponding to theforeground is moving with constant velocity. By utilizing thischaracteristic, an equation in which the mixture ratio α and the sum fof the foreground components are approximated in the spatial directioncan hold true. Also, an equation in which a set of the pixel value of apixel belonging to the mixed area and the pixel value of a pixelbelonging to the background area is established in accordance with theamount of movement v of the foreground. In the mixture-ratio calculator104 having the configuration shown in FIG. 63, by utilizing a pluralityof sets of the pixel values of the pixels belonging to the mixed areaand the pixel values of the pixels belonging to the background area inaccordance with the movement of the foreground, the equations in whichthe mixture ratio α and the sum f of the foreground components areapproximated are solved.

When a change in the mixture ratio α is approximated as a straight line,the mixture ratio α can be expressed by equation (92).α+il+p   (92)In equation (92), i indicates the spatial index when the position of thedesignated pixel is set to 0, 1 designates the gradient of the straightline of the mixture ratio α, and p designates the intercept of thestraight line of the mixture ratio α and also indicates the mixtureratio α of the designated pixel. In equation (92), the index i is known,and the gradient 1 and the intercept p are unknown.

The relationship among the index i, the gradient l, and the intercept pis shown in FIG. 64.

By approximating the mixture ratio α as equation (92), a plurality ofdifferent mixture ratios a for a plurality of pixels can be expressed bytwo variables. In the example shown in FIG. 64, the five mixture ratiosfor five pixels are expressed by the two variables, i.e., the gradient 1and the intercept p. In FIG. 64, the while dot indicates the designatedpixel, and the black dots indicate the pixels located in close proximitywith the designated pixel.

When the mixture ratio α is approximated in the plane shown in FIG. 65,equation (92) is expanded into the plane by considering the movement vcorresponding to the two directions, i.e., the horizontal direction andthe vertical direction of the image, and the mixture ratio α can beexpressed by equation (93).α=jm+kq+p   (93)In equation (93), j is the index in the horizontal direction and k isthe index in the vertical direction when the position of the designatedpixel is 0. In equation (93), m designates the horizontal gradient ofthe mixture ratio α in the plane, and q indicates the vertical gradientof the mixture ratio α in the plane. In equation (93), p indicates theintercept of the mixture ratio α in the plane. In FIG. 65, the white dotindicates the designated pixel.

For example, in frame #n shown in FIG. 51, equations (94) through (96)can hold true for C05 through C07, respectively.C 05=α05·B 05/v+f 05   (94)C 06=α06·B 06/v+f 06   (95)C 07=α07·B 07/v+f 07   (96)

Assuming that the foreground components positioned in close proximitywith each other are equal to each other, i.e., that F01 through F03 areequal, equation (97) holds true by replacing F01 through F03 by fc.f(x)=(1−α(x))·Fc   (97)In equation (97), x indicates the position in the spatial direction.

When α(x) is replaced by equation (93), equation (97) can be expressedby equation (98). $\begin{matrix}\begin{matrix}{{f(x)} = {( {1 - ( {{jm} + {kq} + p} )} ) \cdot {Fc}}} \\{= {{j \cdot ( {{- m} \cdot {Fc}} )} + {k \cdot ( {{- q} \cdot {Fc}} )} + ( {( {1 - p} ) \cdot {Fc}} )}} \\{= {{js} + {kt} + u}}\end{matrix} & (98)\end{matrix}$

In equation (98), (−m·Fc), (−q˜Fc), and (1−p)·Fc are replaced, asexpressed by equations (99) through (101), respectively.s=−m·Fc   (99)t=−q·Fc   (100)u=(1−p)·Fc   (101)

In equation (98), j is the index in the horizontal direction and k isthe index in the vertical direction when the position of the designatedpixel is 0.

As discussed above, since it can be assumed that the objectcorresponding to the foreground is moving with constant velocity withinthe shutter period, and that the foreground components positioned inclose proximity with each other are uniform, the sum of the foregroundcomponents can be approximated by equation (98).

When the mixture ratio α is approximated by a straight line, the sum ofthe foreground components can be expressed by equation (102).f(x)=is+u   (102)

By replacing the mixture ratio α and the sum of the foregroundcomponents in equation (92) by using equations (93) and (98), the pixelvalue M can be expressed by equation (103). $\begin{matrix}\begin{matrix}{M = {{( {{jm} + {kq} + p} ) \cdot B} + {js} + {kt} + u}} \\{= {{{jB} \cdot m} + {{kB} \cdot q} + {B \cdot p} + {j \cdot s} + {k \cdot t} + u}}\end{matrix} & (103)\end{matrix}$

In equation (103), unknown variables are six factors, such as thehorizontal gradient m of the mixture ratio α in the plane, the verticalgradient q of the mixture ratio α in the plane, and the intercepts ofthe mixture ratio α in the plane, p, s, t, and u.

It is now assumed for a plurality of frames that an object correspondingto the foreground is moving with constant velocity, and that theforeground components are uniform. Then, the approximation in one frameshown in FIG. 65 can be expanded into the approximation over a pluralityof frames. In FIG. 66, A indicates planes of the mixture ratio and theforeground components. In FIG. 66, the block dots designate pixels tobelong to the mixed area.

It is assumed in FIG. 66 that the gradients of the planes in theindividual frames are the same, and the pixel value can be expressed byequation (103) by the approximation of the mixture ratio and theforeground components.

Accordingly, equation (103) can be modified into equation (104) when theindex in the time direction is T.M _(T) =jB _(T) ·m+kB _(T) +q+B _(T) ·p+j·s+k·t+u   (104)

The pixel value B and the pixel value M are set in equation (104) inaccordance with the amount of movement of the object, which is thedesignated pixel, and the pixels close to the designated pixel in eachframe, and then, a plurality of equations in which the pixel-value M andthe pixel value B are set are solved by the method of least squares,thereby calculating the mixture ratio α.

It is now assumed, for example, that the horizontal index j of thedesignated pixel is set to 0, the vertical index k of the designatedpixel is set to 0, and the index T in the time direction is set to 0. Inthis case, when the pixel value M or the pixel value B is set in theequation indicating the mixed pixel and expressed by equation (104) for3×3 pixels located in the proximity with the designated pixel, equations(105) through (113) are obtained.M _(0,−1,−1)=(−1)·B _(0,−1,−1) ·m+(−1)·B _(0,−1,−1) ·q+B _(0,−1,−1)·p+(−1)·s+(−1)·t+u   (105)M _(0,0,−1)=(0)·B _(0,0,−1) ·m+(−1)·B _(0,0,−1) ·q+B _(0,0,−1)·p+(0)·s+(−1)·t+u   (106)M _(0,+1,−1)=(+1)·B _(0,+1,−1) ·m+(−1)·B _(0,+1,−1) q+B _(0,+1,−1)·p+(+1)·s+(−1)·t+u   (107)M _(0,−1,0)=(−1)·B _(0,−1,0) ·m+(0)·B _(0,−1,0) q+B _(0,−1,0)·p+(−1)·s+(0)·t+u   (108)M _(0,0,0)=(0)·B _(0,0,0) ·m+(0)·B _(0,0,0) ·q+B _(0,0,0)·p+(0)·s+(0)·t+u   (109)M _(0,+1,0)=(+1)·B _(0,+1,0) ·m+(0)·B _(0,+1,0) ·q+B _(0,+1,0)·p+(+1)·s+(0)·t+u   (110)M _(0,−1,+1)=(−1)·B _(0,−1,+1) ·m+(+1)·B _(0,−1,+1) ·q+B _(0,−1,+1)·p+(−1)·s+(+1)·t+u   (111)M _(0,0,+1)=(0)·B _(0,0,+1) ·m+(+1)·B _(0,0,+1) ·q+B _(0,0,+1)·p+(0)·s+(+1)·t+u   (112)M _(0,+1,+1)=(+1)·B _(0,+1,+1) ·m+(+1)·B _(0,+1,+1) ·q+B _(0,+1,+1)·p+(+1)·s+(+1)·t+u   (113)

Since the horizontal index j of the designated pixel is 0, and thevertical index k of the designated pixel is 0, the mixture ratio α ofthe designated pixel is equal to the value when j is 0 and k is 0 inequation (93), i.e., the mixture ratio α is equal to the intercept p inequation (93).

Accordingly, based on 27 equations (9×3), i.e., equations (105) through(113) considering when T is −1, 0, and 1, the horizontal gradient m, thevertical gradient q, and the intercepts p, 5, t, and u are calculated bythe method of least squares, and the intercept p is output as themixture ratio α.

A specific process for calculating the mixture ratio a by applying themethod of least squares is as follows.

When the index T, the index i, and the index k are expressed by a singleindex x, the relationship among the index T, the index i, the index k,and the index x can be expressed by equation (114).x=(T+1)·3·(j+1)·3+(k+1)   (114)

It is now assumed that the horizontal gradient m, the vertical gradientq, and the intercepts p, s, t, and u are expressed by variables w0, w1,w2, w3, w4, and w5, respectively, and jB, kB, B, j, k and 1 areexpressed by a0, a1, a2, a3, a4, and a5, respectively. In considerationof the error ex, equations (105) through (113) can be modified intoequation (115). $\begin{matrix}{{M\quad x} = {{\sum\limits_{y = 0}^{5}{{ay} \cdot {wy}}} + {ex}}} & (115)\end{matrix}$In equation (115), x is any one of the integers from 0 to 27.

Equation (116) can be found from equation (115). $\begin{matrix}{{ex} = {{M\quad x} - {\sum\limits_{y = 0}^{5}{{ay} \cdot {wy}}}}} & (116)\end{matrix}$

Since the method of least squares is applied, the square sum E of theerror is defined as follows, as expressed by equation (117).$\begin{matrix}{E = {\sum\limits_{x = 0}^{8}{ex}^{2}}} & (117)\end{matrix}$

In order to minimize the error, the partial differential value of thevariable Wv with respect to the square sum E of the error should be 0. vis any one of the integers from 0 to 5. Thus, wy is determined so thatequation (118) is satisfied. $\begin{matrix}\begin{matrix}{\frac{\partial E}{\partial{Wv}} = {2 \cdot {\sum\limits_{x = 0}^{8}{{ex} \cdot \frac{\partial{ex}}{\partial{Wv}}}}}} \\{= {{2 \cdot {\sum\limits_{x = 0}^{\square}{{ex} \cdot {av}}}} = 0}}\end{matrix} & (118)\end{matrix}$

By substituting equation (116) into equation (118), equation (119) isobtained. $\begin{matrix}{{\sum\limits_{x = 0}^{8}( {{av} \cdot {\sum\limits_{y = 0}^{5}{{ay} \cdot {Wy}}}} )} = {\sum\limits_{x = 0}^{8}{{{av} \cdot M}\quad x}}} & (119)\end{matrix}$

For example, the sweep-out method (Gauss-Jordan elimination) is appliedto the normal equations consisting of six equations obtained bysubstituting one of the integers from 0 to 5 into v in equation (119),thereby obtaining wy. As stated above, w0 is the horizontal gradient m,w1 is the vertical gradient q, w2 is the intercept p, w3 is s, w4 is t,and w5 is u.

As discussed above, by applying the method of least squares to theequations in which the pixel value M and the pixel value B are set, thehorizontal gradient m, the vertical gradient q, and the intercepts p, s,t, and u can be determined.

The intercept p is the mixture ratio α when indexes i and k are 0, i.e.,the intercept p is located at the center position. Thus, the intercept Pis output.

A description has been given with reference to equations (105) through(113), by assuming that the pixel value of the pixel contained in themixed area is M, and the pixel value of the pixel contained in thebackground area is B. In this case, it is necessary to set normalequations for each of the cases where the designated pixel is containedin the covered background area, or the designated pixel is contained inthe uncovered background area.

For example, if the mixture ratio α of the pixel contained in thecovered background area in frame #n shown in FIG. 51 is determined, C04through C08 of the pixels in frame #n and the pixel values P04 throughP08 of the pixels in frame #n−1 are set in the normal equations.

If the mixture ratio α of the pixels contained in the uncoveredbackground area in frame #n shown in FIG. 52 is determined, C28 throughC32 of the pixels in frame #n and the pixel values N28 through N32 ofthe pixels in frame #n+1 are set in the normal equations.

Moreover, if, for example, the mixture ratio α of the pixel contained inthe covered background area shown in FIG. 67 is calculated, thefollowing equations (120) through (128) are set. The pixel value of thepixel for which the mixture ratio α is calculated is Mc5. In FIG. 67,the white dots indicate pixels to belong to the background, and theblack dots indicate pixels to belong to the mixed area.Mc _(T) 1=(−1)·Bc 1·m+(−1)·Bc 1·q+Bc 1·p+(−1)·s+(−1)·t+u   (120)Mc _(T) 2=(0)·Bc 2·m+(−1)·Bc 2·q+Bc 2·p+(0)·s+(−1)·t+u   (121)Mc _(T) 3=(+1)·Bc 3·m+(−1)·Bc 3·q+Bc 3·p+(+1)·s+(−1)·t+u   (122)Mc _(T) 4=(−1)·Bc 4·m+(0)·Bc 4·q+Bc 4·p+(−1)·s+(0)·t+u   (123)Mc _(T) 5=(0)·Bc 5·m+(0)·Bc 5·q+Bc 5·p+(0)·s+(0)·t+u   (124)Mc _(T) 6=(+1)·Bc 6·m+(0)·Bc 6·q+Bc 6·p+(+1)·s+(0)·t+u   (125)Mc _(T) 7=(−1)·Bc 7·m+(+1)·Bc 7·q+Bc 7·p+(−1)·s+(+1)·t+u   (126)Mc _(T) 8=(0)·Bc 8·m+(+1)·Bc 8·q+Bc 8·p+(0)·s+(+1)·t+u   (127)Mc _(T) 9=(+1)·Bc 9·m+(+1)·Bc 9·q+Bc 9·p+(+1)·s+(+1)·t+u   (128)

For calculating the mixture ratio α of the pixel contained in thecovered background area in frame #n, the pixel values Bc1 through Bc9 ofthe pixels of the background area in frame #n−1 in equations (120)through (128), respectively, corresponding to the pixels in frame #n areused when T is 0.

When, for example, the mixture ratio α of the pixel contained in theuncovered background area shown in FIG. 67 is calculated, the followingequations (129) through (137) are set. The pixel value of the pixel forwhich the mixture ratio α is calculated is Mu5.Mu _(T) 1=(−1)·Bu 1·m+(−1)·Bu 1·q+Bu 1·p+(−1)·s+(−1)·t+u   (129)Mu _(T) 2=(0)·Bu 2·m+(−1)·Bu 2·q+Bu 2·p+(0)·s+(−1)·t+u   (130)Mu _(T) 3=(+1)·Bu 3·m+(−1)·Bu 3·q+Bu 3·p+(+1)·s+(−1)·t+u   (131)Mu _(T) 4=(−1)·Bu 4·m+(0)·Bu 4·q+Bu 4·p+(−1)·s+(0)·t+u   (132)Mu _(T) 5=(0)·Bu 5·m+(0)·Bu 5·q+Bu 5·p+(0)·s+(0)·t+u   (133)Mu _(T) 6=(+1)·Bu 6·m+(0)·Bu 6·q+Bu 6·p+(+1)·s+(0)·t+u   (134)Mu _(T) 7=(−1)·Bu 7·m+(+1)·Bu 7·q+Bu 7·p+(−1)·s+(+1)·t+u   (135)Mu _(T) 8=(0)·Bu 8·m+(+1)·Bu 8·q+Bu 8·p+(0)·s+(+1)·t+u   (136)Mu _(T) 9=(+1)·Bu 9·m+(+1)·Bu 9·q+Bu 9·p+(+1)·s+(+1)·t+u   (137)

For calculating the mixture ratio α of the pixel contained in theuncovered background area in frame #n, the pixel values Bu1 through Bu9of the pixels of the background area in frame #n+1 in equations (129)through (137), respectively, corresponding to the pixels in frame #n areused when T is 0.

FIG. 68 is a block diagram illustrating the configuration of theestimated-mixture-ratio processor 501 for calculating the estimatedmixture ratio by using the amount of movement v based on a modelcorresponding to the covered background area.

A frame memory 521 stores a plurality of frames of an input image andsupplies the stored frames to a mixture-ratio calculator 522. The framememory 521 stores, for example, six frames, in units of frames, andsupplies the stored six frames to the mixture-ratio calculator 522.

The mixture-ratio calculator 522 stores a normal equation forcalculating the mixture ratio α and the sum f of the foregroundcomponents in advance.

The mixture-ratio calculator 522 sets in the normal equation a pixelvalue belonging to the mixed area and the corresponding pixel valuebelonging to the background area contained in the frames supplied fromthe frame memory 521. The mixture-ratio calculator 522 solves the normalequation in which the pixel value belonging to the mixed area and thecorresponding pixel value belonging to the background area are setaccording to a matrix solution method so as to obtain the estimatedmixture ratio, and outputs the calculated estimated mixture ratio.

FIG. 69 is a block diagram illustrating the configuration of themixture-ratio calculator 522.

A normal-equation adder 541 stores a normal equation for calculating theestimated mixture ratio in advance.

The normal-equation adder 541 sets in the normal equation acorresponding value belonging to the mixed area and the correspondingvalue belonging to the background area contained in an image of M framessupplied from the frame memory 521. The normal-equation adder 541supplies the normal equation in which the pixel value belonging to themixed area and the corresponding pixel value belonging to the backgroundarea are set to a normal-equation calculator 542.

The normal-equation calculator 542 solves the normal equation in whichthe pixel values are set supplied from the normal-equation adder 541 byapplying, for example, a sweep-out method (Gauss-Jordan elimination) soas to obtain the estimated mixture ratio, and outputs the calculatedmixture ratio.

As discussed above, the estimated-mixture-ratio processor 501 calculatesthe estimated mixture ratio by using the amount of movement v based on amodel corresponding to the covered background area.

The estimated-mixture-ratio processor 502 has a configuration similar tothe estimated-mixture-ratio processor 501, and an explanation thereof isthus omitted.

The mixture-ratio determining portion 503 sets the mixture ratio basedon the area information supplied from the area specifying unit 101 andindicating to which of the foreground area, the background area, thecovered background area, or the uncovered background area the pixel forwhich the mixture ratio is to be calculated belongs. The mixture-ratiodetermining portion 503 sets the mixture ratio to 0 when thecorresponding pixel belongs to the foreground area, and sets the mixtureratio to 1 when the corresponding pixel belongs to the background area.When the corresponding pixel belongs to the covered background area, themixture-ratio determining portion 503 sets the mixture ratio to theestimated mixture ratio supplied from the estimated-mixture-ratioprocessor 501. When the corresponding pixel belongs to the uncoveredbackground area, the mixture-ratio determining portion 503 sets themixture ratio to the estimated mixture ratio supplied from theestimated-mixture-ratio processor 502. The mixture-ratio determiningportion 503 outputs the mixture ratio which has been set based on thearea information.

The mixture-ratio calculation processing performed by the mixture-ratiocalculator 102 configured shown in FIG. 63 is discussed below withreference to the flowchart of FIG. 70. In step S501, the mixture-ratiocalculator 102 obtains area information supplied from the areaspecifying unit 101. In step S502, the estimated-mixture-ratio processor501 executes the processing for estimating the mixture ratio by using amodel corresponding to a covered background area, and supplies theestimated mixture ratio to the mixture-ratio determining portion 503.Details of the processing for estimating the mixture ratio are discussedbelow with reference to the flowchart of FIG. 71.

In step S503, the estimated-mixture-ratio processor 502 executes theprocessing for estimating the mixture ratio by using a modelcorresponding to an uncovered background area, and supplies theestimated mixture ratio to the mixture-ratio determining portion 503.

In step S504, the mixture-ratio calculator 102 determines whether themixture ratios have been estimated for the whole frame. If it isdetermined that the mixture ratios have not yet been estimated for thewhole frame, the process returns to step S502, and the processing forestimating the mixture ratio for the subsequent pixel is executed.

If it is determined in step S504 that the mixture ratios have beenestimated for the whole frame, the process proceeds to step S505. Instep S505, the mixture-ratio determining portion 503 sets the mixtureratio based on the area information supplied from the area specifyingunit 101 and indicating to which of the foreground area, the backgroundarea, the covered background area, or the uncovered background area thepixel for which the mixture ratio is to be calculated belongs. Themixture-ratio determining portion 503 sets the mixture ratio to 0 whenthe corresponding pixel belongs to the foreground area, and sets themixture ratio to 1 when the corresponding pixel belongs to thebackground area. When the corresponding pixel belongs to the coveredbackground area, the mixture-ratio determining portion 503 sets theestimated mixture ratio supplied from the estimated-mixture-ratioprocessor 501 as the mixture ratio. When the corresponding pixel belongsto the uncovered background area, the mixture-ratio determining portion503 sets the estimated mixture ratio supplied from theestimated-mixture-ratio processor 502 as the mixture ratio. Theprocessing is then completed.

As discussed above, the mixture-ratio calculator 102 is able tocalculate the mixture ratio α, which indicates a feature quantitycorresponding to each pixel, based on the area information supplied fromthe area specifying unit 101, and the input image.

By utilizing the mixture ratio α, it is possible to separate theforeground components and the background components contained in thepixel values while maintaining the information of motion blur containedin the image corresponding to the moving object.

A description is now given, with reference to the flowchart of FIG. 71,of the mixture-ratio estimating processing by using a model of thecovered background area in step S502 of FIG. 70.

In step S521, the normal-equation adder 541 sets the pixel valuecontained in the input image in a normal equation corresponding to amodel of the covered background area.

In step S522, the normal-equation adder 541 determines whether thesetting of the target pixels is finished. If it is determined that thesetting of the target pixels is not finished, the process returns tostep S521, and the processing for setting the pixel values in the normalequation is repeated.

If it is determined in step S522 that the setting for the target pixelsis finished, the process proceeds to step S523. In step S523, thenormal-equation calculator 542 calculates the estimated mixture ratiobased on the normal equations in which the pixels values are set, andoutputs the calculated mixture ratio.

As discussed above, the estimated-mixture-ratio processor 501 is able tocalculate the estimated mixture ratio based on the input image.

The mixture-ratio estimating processing by using a model correspondingto the uncovered background area in step S503 of FIG. 70 is similar tothe processing indicated by the flowchart of FIG. 71 by using the normalequations corresponding to a model of the uncovered background area, andan explanation thereof is thus omitted.

The embodiment has been described, assuming that the objectcorresponding to the background is stationary. However, theabove-described mixture-ratio calculation processing can be applied evenif the image corresponding to the background area contains motion. Forexample, if the image corresponding to the background area is uniformlymoving, the estimated-mixture-ratio processor 501 shifts the overallimage in accordance with this motion, and performs processing in amanner similar to the case in which the object corresponding to thebackground is stationary. If the image corresponding to the backgroundarea contains locally different motions, the estimated-mixture-ratioprocessor 501 selects the pixels corresponding to the motions as thepixels belonging to the mixed area, and executes the above-describedprocessing.

The mixture-ratio calculator 104 may execute the mixture-ratioestimating processing on all the pixels only by using a modelcorresponding to the covered background area, and outputs the calculatedestimated mixture ratio as the mixture ratio α. In this case, themixture ratio α indicates the ratio of the background components for thepixels belonging to the covered background area, and indicates the ratioof the foreground components for the pixels belonging to the uncoveredbackground area.

Concerning the pixels belonging to the uncovered background area, theabsolute value of the difference between the calculated mixture ratio αand 1 is determined, and the calculated absolute value is set as themixture ratio α. Then, the signal processor 12 is able to determine themixture ratio α indicating the ratio of the background components forthe pixels belonging to the uncovered background area.

Similarly, the mixture-ratio processor 104 may execute the mixture-ratioestimating processing on all the pixels only by using a modelcorresponding to the uncovered background area, and outputs thecalculated estimated mixture ratio as the mixture ratio α.

The foreground/background separator 105 is discussed below. FIG. 72 is ablock diagram illustrating an example of the configuration of theforeground/background separator 105. The input image supplied to theforeground/background separator 105 is supplied to a separating portion601, a switch 602, and a switch 604. The area information supplied fromthe area specifying unit 103 and indicating the information of thecovered background area and the uncovered background area is supplied tothe separating portion 601. The area information indicating theforeground area is supplied to the switch 602. The area informationindicating the background area supplied to the switch 604.

The mixture ratio ax supplied from the mixture-ratio calculator 104 issupplied to the separating portion 601.

The separating portion 601 separates the foreground components from theinput image based on the area information indicating the coveredbackground area, the area information indicating the uncoveredbackground area, and the mixture ratio a, and supplies the separatedforeground components to a synthesizer 603. The separating portion 601also separates the background components from the input image, andsupplies the separated background components to a synthesizer 605.

The switch 602 is closed when a pixel corresponding to the foreground isinput based on the area information indicating the foreground area, andsupplies only the pixels corresponding to the foreground contained inthe input image to the synthesizer 603.

The switch 604 is closed when a pixel corresponding to the background isinput based on the area information indicating the background area, andsupplies only the pixels corresponding to the background contained inthe input image to the synthesizer 605.

The synthesizer 603 synthesizes a foreground component image based onthe foreground components supplied from the separating portion 601 andthe pixels corresponding to the foreground supplied from the switch 602,and outputs the synthesized foreground component image. Since theforeground area and the mixed area do not overlap, the synthesizer 603applies, for example, logical OR to the foreground components and theforeground pixels, thereby synthesizing the foreground component image.

In the initializing processing executed at the start of the synthesizingprocessing for the foreground component image, the synthesizer 603stores an image whose pixel values are all 0 in a built-in frame memory.Then, in the synthesizing processing for the foreground component image,the synthesizer 603 stores the foreground component image (overwritesthe previous image by the foreground component image). Accordingly, 0 isstored in the pixels corresponding to the background area in theforeground component image output from the synthesizer 603.

The synthesizer 605 synthesizes a background component image based onthe background components supplied from the separating portion 601 andthe pixels corresponding to the background supplied from the switch 604,and outputs the synthesized background component image. Since thebackground area and the mixed area do not overlap, the synthesizer 605applies, for example, logical OR to the background components and thebackground pixels, thereby synthesizing the background component image.

In the initializing processing executed at the start of the synthesizingprocessing for the background component image, the synthesizer 605stores an image whose pixel values are all 0 in a built-in frame memory.Then, in the synthesizing processing for the background component image,the synthesizer 605 stores the background component image (overwritesthe previous image by the background component image). Accordingly, 0 isstored in the pixels corresponding to the foreground area in thebackground component image output from the synthesizer 605.

FIG. 73A illustrates the input image input into theforeground/background separator 105 and the foreground component imageand the background component image output from the foreground/backgroundseparator 105. FIG. 73B illustrates a model corresponding to the inputimage input into the foreground/background separator 105 and theforeground component image and the background component image outputfrom the foreground/background separator 105.

FIG. 73A is a schematic diagram illustrating the image to be displayed,and FIG. 73B is a model obtained by expanding in the time direction thepixels disposed in one line including the pixels belonging to theforeground area, the pixels belonging to the background area, and thepixels belonging to the mixed area corresponding to FIG. 73A.

As shown in FIGS. 73A and 73B, the background component image outputfrom the foreground/background separator 105 consists of the pixelsbelonging to the background area and the background components containedin the pixels of the mixed area.

As shown in FIGS. 73A and 73B, the foreground component image outputfrom the foreground/background separator 105 consists of the pixelbelonging to the foreground area and the foreground components containedin the pixels of the mixed area.

The pixel values of the pixels in the mixed area are separated into thebackground components and the foreground components by theforeground/background separator 105. The separated background componentsform the background component image together with the pixels belongingto the background area. The separated foreground components form theforeground component image together with the pixels belonging to theforeground area.

As discussed above, in the foreground component image, the pixel valuesof the pixels corresponding to the background area are set to 0, andsignificant pixel values are set in the pixels corresponding to theforeground area and the pixels corresponding to the mixed area.Similarly, in the background component image, the pixel values of thepixels corresponding to the foreground area are set to 0, andsignificant pixel values are set in the pixels corresponding to thebackground area and the pixels corresponding to the mixed area.

A description is given below of the processing executed by theseparating portion 601 for separating the foreground components and thebackground components from the pixels belonging to the mixed area.

FIG. 74 illustrates a model of an image indicating foreground componentsand background components in two frames including a foreground objectmoving from the left to the right in FIG. 74. In the model of the imageshown in FIG. 74, the amount of movement v is 4, and the number ofvirtual divided portions is 4.

In frame #n, the leftmost pixel and the fourteenth through eighteenthpixels from the left consist of only the background components andbelong to the background area. In frame #n, the second through fourthpixels from the left contain the background components and theforeground components, and belong to the uncovered background area. Inframe #n, the eleventh through thirteenth pixels from the left containbackground components and foreground components, and belong to thecovered background area. In frame #n, the fifth through tenth pixelsfrom the left consist of only the foreground components, and belong tothe foreground area.

In frame #n+1, the first through fifth pixels from the left and theeighteenth pixel from the left consist of only the backgroundcomponents, and belong to the background area. In frame #n+1, the sixththrough eighth pixels from the left contain background components andforeground components, and belong to the uncovered background area. Inframe #n+1, the fifteenth through seventeenth pixels from the leftcontain background components and foreground components, and belong tothe covered background area. In frame #n+1, the ninth through fourteenthpixels from the left consist of only the foreground components, andbelong to the foreground area.

FIG. 75 illustrates the processing for separating the foregroundcomponents from the pixels belonging to the covered background area. InFIG. 75, α1 through α18 indicate mixture ratios of the individual pixelsof frame #n. In FIG. 75, the fifteenth through seventeenth pixels fromthe left belong to the covered background area.

The pixel value C15 of the fifteenth pixel from the left in frame #n canbe expressed by equation (138): $\begin{matrix}\begin{matrix}{{C15} = {{{B15}/v} + {{F09}/v} + {{F08}/v} + {{F07}/v}}} \\{= {{\alpha\quad{15 \cdot {B15}}} + {{F09}/v} + {{F08}/v} + {{F07}/v}}} \\{= {{{\alpha 15} \cdot {P15}} + {{F09}/v} + {{F08}/v} + {{F07}/v}}}\end{matrix} & (138)\end{matrix}$where α15 indicates the mixture ratio of the fifteenth pixel from theleft in frame #n, and P15 designates the pixel value of the fifteenthpixel from the left in frame #n−1.

The sum f15 of the foreground components of the fifteenth pixel from theleft in frame #n can be expressed by equation (139) based on equation(138). $\begin{matrix}\begin{matrix}{{f15} = {{{F09}/v} + {{F08}/v} + {{F07}/v}}} \\{= {{C15} - {{\alpha 15} \cdot {P15}}}}\end{matrix} & (139)\end{matrix}$

Similarly, the sum f16 of the foreground components of the sixteenthpixel from the left in frame #n can be expressed by equation (140), andthe sum f17 of the foreground components of the seventeenth pixel fromthe left in frame #n can be expressed by equation (141).f 16=C 16−α16·P 16   (140)f 17=C 17−α17·P 17   (141)

In this manner, the foreground components fc contained in the pixelvalue C of the pixel belonging to the covered background area can beexpressed by equation (142):fc=C−α·P   (142)where P designates the pixel value of the corresponding pixel in theprevious frame.

FIG. 76 illustrates the processing for separating the foregroundcomponents from the pixels belonging to the uncovered background area.In FIG. 76, α1 through α18 indicate mixture ratios of the individualpixels of frame #n. In FIG. 76, the second through fourth pixels fromthe left belong to the uncovered background area.

The pixel value C02 of the second pixel from the left in frame #n can beexpressed by equation (143) $\begin{matrix}\begin{matrix}{{C02} = {{{B02}/v} + {{B02}/v} + {{B02}/v} + {{F01}/v}}} \\{= {{{\alpha 2} \cdot {B02}} + {{F01}/v}}} \\{= {{{\alpha 2} \cdot {N02}} + {{F01}/v}}}\end{matrix} & (143)\end{matrix}$where α2 indicates the mixture ratio of the second pixel from the leftin frame #n, and N02 designates the pixel value of the second pixel fromthe left in frame #n+1.

The sum f02 of the foreground components of the second pixel from theleft in frame #n can be expressed by equation (144) based on equation(143). $\begin{matrix}\begin{matrix}{{f02} = {{F01}/v}} \\{= {{C02} - {{\alpha 2} \cdot {N02}}}}\end{matrix} & (144)\end{matrix}$

Similarly, the sum f03 of the foreground components of the third pixelfrom the left in frame #n can be expressed by equation (145), and thesum f04 of the foreground components of the fourth pixel from the leftin frame #n can be expressed by equation (146).f 03=C 03−α3·N 03   (145)f 04=C 04−α4·N 04   (146)

In this manner, the foreground components fu contained in the pixelvalue C of the pixel belonging to the uncovered background area can beexpressed by equation (147):fu=C−α·N   (147)where N designates the pixel value of the corresponding pixel in thesubsequent frame.

As discussed above, the separating portion 601 is able to separate theforeground components from the pixels belonging to the mixed area andthe background components from the pixels belonging to the mixed areabased on the information indicating the covered background area and theinformation indicating the uncovered background area contained in thearea information, and the mixture ratio a for each pixel.

FIG. 77 is a block diagram illustrating an example of the configurationof the separating portion 601 for executing the above-describedprocessing. An image input into the separating portion 601 is suppliedto a frame memory 621, and the area information indicating the coveredbackground area and the uncovered background area supplied from themixture-ratio calculator 104 and the mixture ratio a are supplied to aseparation processing block 622.

The frame memory 621 stores the input images in units of frames. When aframe to be processed is frame #n, the frame memory 621 stores frame#n−1, which is the frame one frame before frame #n, frame #n, and frame#n+1, which is the frame one frame after frame #n.

The frame memory 621 supplies the corresponding pixels in frame #n−1,frame #n, and frame #n+1 to the separation processing block 622.

The separation processing block 622 applies the calculations discussedwith reference to FIGS. 75 and 76 to the pixel values of thecorresponding pixels in frame #n−1, frame #n, and frame #n+1 suppliedfrom the frame memory 621 based on the area information indicating thecovered background area and the uncovered background area and themixture ratio α so as to separate the foreground components and thebackground components from the pixels belonging to the mixed area inframe #n, and supplies them to a frame memory 623.

The separation processing block 622 is formed of an uncovered areaprocessor 631, a covered area processor 632, a synthesizer 633, and asynthesizer 634.

A multiplier 641 of the uncovered area processor 631 multiplies thepixel value of the pixel in frame #n+1 supplied from the frame memory621 by the mixture ratio α, and outputs the resulting pixel value to aswitch 642. The switch 642 is closed when the pixel of frame #n(corresponding to the pixel in frame #n+1) supplied from the framememory 621 belongs to the uncovered background area, and supplies thepixel value multiplied by the mixture ratio a supplied from themultiplier 641 to a calculator 643 and the synthesizer 634. The valueobtained by multiplying the pixel value of the pixel in frame #n+1 bythe mixture ratio a output from the switch 642 is equivalent to thebackground components of the pixel value of the corresponding pixel inframe #n.

The calculator 643 subtracts the background components supplied from theswitch 642 from the pixel value of the pixel in frame #n supplied fromthe frame memory 621 so as to obtain the foreground components. Thecalculator 643 supplies the foreground components of the pixel in frame#n belonging to the uncovered background area to the synthesizer 633.

A multiplier 651 of the covered area processor 632 multiplies the pixelvalue of the pixel in frame #n−1 supplied from the frame memory 621 bythe mixture ratio a, and outputs the resulting pixel value to a switch652. The switch 652 is closed when the pixel of frame #n (correspondingto the pixel in frame #n−1) supplied from the frame memory 621 belongsto the covered background area, and supplies the pixel value multipliedby the mixture ratio a supplied from the multiplier 651 to a calculator653 and the synthesizer 634. The value obtained by multiplying the pixelvalue of the pixel in frame #n−1 by the mixture ratio a output from theswitch 652 is equivalent to the background components of the pixel valueof the corresponding pixel in frame #n.

The calculator 653 subtracts the background components supplied from theswitch 652 from the pixel value of the pixel in frame #n supplied fromthe frame memory 621 so as to obtain the foreground components. Thecalculator 653 supplies the foreground components of the pixel in frame#n belonging to the covered background area to the synthesizer 633.

The synthesizer 633 combines the foreground components of the pixelsbelonging to the uncovered background area and supplied from thecalculator 643 with the foreground components of the pixels belonging tothe covered background area and supplied from the calculator 653, andsupplies the synthesized foreground components to the frame memory 623.

The synthesizer 634 combines the background components of the pixelsbelonging to the uncovered background area and supplied from the switch642 with the background components of the pixels belonging to thecovered background area and supplied from the switch 652, and suppliesthe synthesized background components to the frame memory 623.

The frame memory 623 stores the foreground components and the backgroundcomponents of the pixels in the mixed area of frame #n supplied from theseparation processing block 622.

The frame memory 623 outputs the stored foreground components of thepixels in the mixed area in frame #n and the stored backgroundcomponents of the pixels in the mixed area in frame #n.

By utilizing the mixture ratio a, which indicates the feature quantity,the foreground components and the background components contained in thepixel values can be completely separated.

The synthesizer 603 combines the foreground components of the pixels inthe mixed area in frame #n output from the separating portion 601 withthe pixels belonging to the foreground area so as to generate aforeground component image. The synthesizer 605 combines the backgroundcomponents of the pixels in the mixed area in frame #n output from theseparating portion 601 with the pixels belonging to the background areaso as to generate a background component image.

FIG. 78A illustrates an example of the foreground component imagecorresponding to frame #n in FIG. 74. The leftmost pixel and thefourteenth pixel from the left consist of only the background componentsbefore the foreground and the background are separated, and thus, thepixel values are set to 0.

The second and fourth pixels from the left belong to the uncoveredbackground area before the foreground and the background are separated.Accordingly, the background components are set to 0, and the foregroundcomponents are maintained. The eleventh through thirteenth pixels fromthe left belong to the covered background area before the foreground andthe background are separated. Accordingly, the background components areset to 0, and the foreground components are maintained. The fifththrough tenth pixels from the left consist of only the foregroundcomponents, which are thus maintained.

FIG. 78B illustrates an example of the background component imagecorresponding to frame #n in FIG. 74. The leftmost pixel and thefourteenth pixel from the left consist of only the background componentsbefore the foreground and the background are separated, and thus, thebackground components are maintained.

The second through fourth pixels from the left belong to the uncoveredbackground area before the foreground and the background are separated.Accordingly, the foreground components are set to 0, and the backgroundcomponents are maintained. The eleventh through thirteenth pixels fromthe left belong to the covered background area before the foreground andthe background are separated. Accordingly, the foreground components areset to 0, and the background components are maintained. The fifththrough tenth pixels from the left consist of only the foregroundcomponents, and thus, the pixel values are set to 0.

The processing for separating the foreground and the background executedby the foreground/background separator 105 is described below withreference to the flowchart of FIG. 79. In step S601, the frame memory621 of the separating portion 601 obtains an input image, and storesframe #n for which the foreground and the background are separatedtogether with the previous frame #n−1 and the subsequent frame #n+1.

In step S602, the separation processing block 622 of the separatingportion 601 obtains area information supplied from the mixture-ratiocalculator 104. In step S603, the separation processing block 622 of theseparating portion 601 obtains the mixture ratio α supplied from themixture-ratio calculator 104.

In step S604, the uncovered area processor 631 extracts the backgroundcomponents from the pixel values of the pixels belonging to theuncovered background area supplied from the frame memory 621 based onthe area information and the mixture ratio α.

In step S605, the uncovered area processor 631 extracts the foregroundcomponents from the pixel values of the pixels belonging to theuncovered background area supplied from the frame memory 621 based onthe area information and the mixture ratio α.

In step S606, the covered area processor 632 extracts the backgroundcomponents from the pixel values of the pixels belonging to the coveredbackground area supplied from the frame memory 621 based on the areainformation and the mixture ratio α.

In step S607, the covered area processor 632 extracts the foregroundcomponents from the pixel values of the pixels belonging to the coveredbackground area supplied from the frame memory 621 based on the areainformation and the mixture ratio α.

In step S608, the synthesizer 633 combines the foreground components ofthe pixels belonging to the uncovered background area extracted in theprocessing of step S605 with the foreground components of the pixelsbelonging to the covered background area extracted in the processing ofstep S607. The synthesized foreground components are supplied to thesynthesizer 603. The synthesizer 603 further combines the pixelsbelonging to the foreground area supplied via the switch 602 with theforeground components supplied from the separating portion 601 so as togenerate a foreground component image.

In step S609, the synthesizer 634 combines the background components ofthe pixels belonging to the uncovered background area extracted in theprocessing of step S604 with the background components of the pixelsbelonging to the covered background area extracted in the processing ofstep S606. The synthesized background components are supplied to thesynthesizer 605. The synthesizer 605 further combines the pixelsbelonging to the background area supplied via the switch 604 with thebackground components supplied from the separating portion 601 so as togenerate a background component image.

In step S610, the synthesizer 603 outputs the foreground componentimage. In step S611, the synthesizer 605 outputs the backgroundcomponent image. The processing is then completed.

As discussed above, the foreground/background separator 105 is able toseparate the foreground components and the background components fromthe input image based on the area information and the mixture ratio α,and outputs the foreground component image consisting of only theforeground components and the background component image consisting ofonly the background components.

Adjustments of the amount of motion blur from a foreground componentimage are described below.

FIG. 80 is a block diagram illustrating an example of the configurationof the motion-blur adjusting unit 106. The motion vector and thepositional information thereof supplied from the motion detector 102 andthe area information supplied from the area specifying unit 103 aresupplied to a unit-of-processing determining portion 801 and amodel-forming portion 802. The area information supplied from theforeground/background separator 105 is supplied to the adder 804.

The unit-of-processing determining portion 801 supplies, together withthe motion vector, the unit of processing that is generated based on themotion vector and the positional information thereof and the areainformation to the model-forming portion 802. The unit-of-processingdetermining portion 801 supplies the generated unit of processing to theadder 804.

As indicated by A in FIG. 81, for example, the unit of processinggenerated by the unit-of-processing determining portion 801 indicatesconsecutive pixels disposed in the moving direction starting from thepixel corresponding to the covered background area of the foregroundcomponent image until the pixel corresponding to the uncoveredbackground area, or indicates consecutive pixels disposed in the movingdirection starting from the pixel corresponding to the uncoveredbackground area until the pixel corresponding to the covered backgroundarea. The unit of processing is formed of two pieces of data whichindicate, for example, the upper left point (which is the position ofthe leftmost or the topmost pixel in the image designated by the unit ofprocessing) and the lower right point.

The model-forming portion 802 forms a model based on the motion vectorand the input unit of processing. More specifically, for example, themodel-forming portion 802 may store in advance a plurality of models inaccordance with the number of pixels contained in the unit ofprocessing, the number of virtual divided portions of the pixel value inthe time direction, and the number of foreground components for eachpixel. The model-forming portion 902 then may select the model in whichthe correlation between the pixel values and the foreground componentsis designated, such as that in FIG. 82, based on the unit of processingand the number of virtual divided portions of the pixel value in thetime direction.

It is now assumed, for example, that the number of pixels correspondingto the unit of processing is 12, and that the amount of movement vwithin the shutter time is 5. Then, the model-forming portion 802 setsthe number of virtual divided portions to 5, and selects a model formedof eight types of foreground components so that the leftmost pixelcontains one foreground component, the second pixel from the leftcontains two foreground components, the third pixel from the leftcontains three foreground components, the fourth pixel from the leftcontains four pixel components, the fifth pixel from the left containsfive foreground components, the sixth pixel from the left contains fiveforeground components, the seventh pixel from the left contains fiveforeground components, the eighth pixel from the left contains fiveforeground components, the ninth pixel from the left contains fourforeground components, the tenth pixel from the left contains threeforeground components, the eleventh pixel from the left contains twoforeground components, and the twelfth pixel from the left contains oneforeground component.

Instead of selecting a model from the prestored models, themodel-forming portion 802 may generate a model based on the motionvector and the unit of processing when the motion vector and the unit ofprocessing are supplied.

The model-forming portion 802 supplies the selected model to an equationgenerator 803.

The equation generator 803 generates an equation based on the modelsupplied from the model-forming portion 802.

A description is given below, with reference to the model of theforeground component image shown in FIG. 82, of equations generated bythe equation generator 803 when the number of foreground components is8, the number of pixels corresponding to the unit of processing is 12,and the amount of movement v is 5.

When the foreground components contained in the foreground componentimage corresponding to the shutter time/v are F01/v through F08/v, therelationships between F01/v through F08/v and the pixel values C01through C12 can be expressed by equations (148) through (159).C 01=F 01/v   (148)C 02=F 02/v+F 01/v   (149)C 03=F 03/v+F 02/v+F 01 v   (150)C 04=F 04/v+F 03/v+F 02/v+F 01 v   (151)C 05=F 05/v+F 04/v+F 03/v+F 02/v+F 01 v   (152)C 06=F 06/v+F 05/v+F 04/v+F 03/v+F 02/v   (153)C 07=F 07/v+F 06/v+F 05/v+F 04/v+F 03/v   (154)C 08=F 08/v+F 07/v+F 06/v+F 05/v+F 04/v   (155)C 09=F 08/v+F 07/v+F 06/v+F 05/v   (156)C 10=F 08/v+F 07/v+F 06/v   (157)C 11=F 08/v+F 07/v   (158)C 12=F 08/v   (159)

The equation generator 803 generates an equation by modifying thegenerated equations. The equations generated by the equation generator803 are indicated by equations (160) though (171). $\begin{matrix}\begin{matrix}{{C01} = {{1 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (160) \\\begin{matrix}{{C02} = {{1 \cdot {{F01}/v}} + {1 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (161) \\\begin{matrix}{{C03} = {{1 \cdot {{F01}/v}} + {1 \cdot {{F02}/v}} + {1 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (162) \\\begin{matrix}{{C04} = {{1 \cdot {{F01}/v}} + {1 \cdot {{F02}/v}} + {1 \cdot {{F03}/v}} + {1 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (163) \\\begin{matrix}{{C05} = {{1 \cdot {{F01}/v}} + {1 \cdot {{F02}/v}} + {1 \cdot {{F03}/v}} + {1 \cdot {{F04}/}}}} \\{v + {1 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (164) \\\begin{matrix}{{C06} = {{0 \cdot {{F01}/v}} + {1 \cdot {{F02}/v}} + {1 \cdot {{F03}/v}} + {1 \cdot {{F04}/}}}} \\{v + {1 \cdot {{F05}/v}} + {1 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (165) \\\begin{matrix}{{C07} = {{0 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {1 \cdot {{F03}/v}} + {1 \cdot {{F04}/}}}} \\{v + {1 \cdot {{F05}/v}} + {1 \cdot {{F06}/v}} + {1 \cdot {{F07}/v}} + {0 \cdot {{F08}/v}}}\end{matrix} & (166) \\\begin{matrix}{{C08} = {{0 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {1 \cdot {{F04}/}}}} \\{v + {1 \cdot {{F05}/v}} + {1 \cdot {{F06}/v}} + {1 \cdot {{F07}/v}} + {1 \cdot {{F08}/v}}}\end{matrix} & (167) \\\begin{matrix}{{C09} = {{0 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {1 \cdot {{F05}/v}} + {1 \cdot {{F06}/v}} + {1 \cdot {{F07}/v}} + {1 \cdot {{F08}/v}}}\end{matrix} & (168) \\\begin{matrix}{{C10} = {{0 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {1 \cdot {{F06}/v}} + {1 \cdot {{F07}/v}} + {1 \cdot {{F08}/v}}}\end{matrix} & (169) \\\begin{matrix}{{C11} = {{0 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {1 \cdot {{F07}/v}} + {1 \cdot {{F08}/v}}}\end{matrix} & (170) \\\begin{matrix}{{C12} = {{0 \cdot {{F01}/v}} + {0 \cdot {{F02}/v}} + {0 \cdot {{F03}/v}} + {0 \cdot {{F04}/}}}} \\{v + {0 \cdot {{F05}/v}} + {0 \cdot {{F06}/v}} + {0 \cdot {{F07}/v}} + {1 \cdot {{F08}/v}}}\end{matrix} & (171)\end{matrix}$

Equations (160) through (171) can be expressed by equation (172).$\begin{matrix}{{Cj} = {\sum\limits_{i = 01}^{08}{{aij} \cdot {{Fi}/v}}}} & (172)\end{matrix}$

In equation (172), j designates the position of the pixel. In thisexample, j has one of the values from 1 to 12. In equation (172), idesignates the position of the foreground value. In this example, i hasone of the values from 1 to 8. In equation (172), aij has the value 0 or1 according to the values of i and j.

Equation (172) can be expressed by equation (173) in consideration ofthe error. $\begin{matrix}{{Cj} = {{\sum\limits_{i = 01}^{08}{{aij} \cdot {{Fi}/v}}} + {ej}}} & (173)\end{matrix}$In equation (173), ej designates the error contained in the designatedpixel Cj.

Equation (173) can be modified into equation (174). $\begin{matrix}{{ej} = {{Cj} - {\sum\limits_{i = 01}^{08}{{aij} \cdot {{Fi}/v}}}}} & (174)\end{matrix}$

In order to apply the method of least squares, the square sum E of theerror is defined as equation (175). $\begin{matrix}{E = {\sum\limits_{j = 01}^{12}{ej}^{2}}} & (175)\end{matrix}$

In order to minimize the error, the partial differential value using thevariable Fk with respect to the square sum E of the error should be 0.Fk is determined so that equation (176) is satisfied. $\begin{matrix}\begin{matrix}{\frac{\partial E}{\partial{Fk}} = {2 \cdot {\sum\limits_{j = 01}^{12}{{ej} \cdot \frac{\partial{ej}}{\partial{Fk}}}}}} \\{= {2 \cdot {\sum\limits_{j = 01}^{12}\{ {{( {{Cj} - {\sum\limits_{i = 01}^{08}{{aij} \cdot {{Fi}/v}}}} ) \cdot ( {{- {akj}}/v} )} = 0} }}}\end{matrix} & (176)\end{matrix}$

In equation (176), since the amount of movement v is a fixed value,equation (177) can be deduced. $\begin{matrix}{{\sum\limits_{j = 01}^{12}{{akj} \cdot ( {{Cj} - {\sum\limits_{i = 01}^{08}{{aij} \cdot {{Fi}/v}}}} )}} = 0} & (177)\end{matrix}$

To expand equation (177) and transpose the terms, equation (178) can beobtained. $\begin{matrix}{{\sum\limits_{j = 01}^{12}( {{akj} \cdot {\sum\limits_{i = 01}^{08}{{aij} \cdot {Fi}}}} )} = {v{\sum\limits_{j = 01}^{12}{{akj} \cdot {Cj}}}}} & (178)\end{matrix}$

Equation (178) is expanded into eight equations by substituting theindividual integers from 1 to 8 into k in equation (178). The obtainedeight equations can be expressed by one matrix equation. This equationis referred to as a “normal equation”.

An example of the normal equation generated by the equation generator803 based on the method of least squares is indicated by equation (179).$\begin{matrix}{{\begin{bmatrix}5 & 4 & 3 & 2 & 1 & 0 & 0 & 0 \\4 & 5 & 4 & 3 & 2 & 1 & 0 & 0 \\3 & 4 & 5 & 4 & 3 & 2 & 1 & 0 \\2 & 3 & 4 & 5 & 4 & 3 & 2 & 1 \\1 & 2 & 3 & 4 & 5 & 4 & 3 & 2 \\0 & 1 & 2 & 3 & 4 & 5 & 4 & 3 \\0 & 0 & 1 & 2 & 3 & 4 & 5 & 4 \\0 & 0 & 0 & 1 & 2 & 3 & 4 & 5\end{bmatrix}\begin{bmatrix}{F01} \\{F02} \\{F03} \\{F04} \\{F05} \\{F06} \\{F07} \\{F08}\end{bmatrix}} = {v \cdot \begin{bmatrix}{\sum\limits_{i = 08}^{12}{Ci}} \\{\sum\limits_{i = 07}^{11}{Ci}} \\{\sum\limits_{i = 06}^{10}{Ci}} \\{\sum\limits_{i = 05}^{09}{Ci}} \\{\sum\limits_{i = 04}^{08}{Ci}} \\{\sum\limits_{i = 03}^{07}{Ci}} \\{\sum\limits_{i = 02}^{06}{Ci}} \\{\sum\limits_{i = 01}^{05}{Ci}}\end{bmatrix}}} & (179)\end{matrix}$

When equation (179) is expressed by A·F=v·C, C, A, and v are known, andF is unknown. A and v are known when the model is formed, while Cbecomes known when the pixel value is input in the addition processing.

By calculating the foreground components according to the normalequation based on the method of least squares, the error contained inthe pixel C can be distributed.

The equation generator 803 supplies the normal equation generated asdiscussed above to the adder 804.

The adder 804 sets, based on the unit of processing supplied from theunit-of-processing determining portion 801, the pixel value C containedin the foreground component image in the matrix equation supplied fromthe equation generator 803. The adder 804 supplies the matrix in whichthe pixel value C is set to a calculator 805.

The calculator 805 calculates the foreground component Fi/v from whichmotion blur is eliminated by the processing based on a solution, such asa sweep-out method (Gauss-Jordan elimination), so as to obtain Ficorresponding to i indicating one of the integers from 1 to 8, which isthe pixel value from which motion blur is eliminated. The calculator 805then outputs the foreground component image consisting of the pixelvalues Fi without motion blur, such as that in FIG. 83, to a motion-bluradder 806 and a selector 807.

In the foreground component image without motion blur shown in FIG. 83,the reason for setting F01 through F08 in C03 through C10, respectively,is not to change the position of the foreground component image withrespect to the screen. However, F01 through F08 may be set in anydesired positions.

The motion-blur adder 806 is able to adjust the amount of motion blur byadding the amount v′ by which motion blur is adjusted, which isdifferent from the amount of movement v, for example, the amount v′ bywhich motion blur is adjusted, which is one half the value of the amountof movement v, or the amount v′ by which motion blur is adjusted, whichis irrelevant to the amount of movement v. For example, as shown in FIG.84, the motion-blur adder 806 divides the foreground pixel value Fiwithout motion blur by the amount v′ by which motion blur is adjusted soas to obtain the foreground component Fi/v′. The motion-blur adder 806then calculates the sum of the foreground components Fi/v′, therebygenerating the pixel value in which the amount of motion blur isadjusted. For example, when the amount v′ by which motion blur isadjusted is 3, the pixel value C02 is set to (F01)/v′, the pixel valueC3 is set to (F01+F02)/v′, the pixel value C04 is set to(F01+F02+F03)/v′, and the pixel value C05 is set to (F02+F03+F04)/v′.

The motion-blur adder 806 supplies the foreground component image inwhich the amount of motion blur is adjusted to a selector 807.

The selector 807 selects one of the foreground component image withoutmotion blur supplied from the calculator 805 and the foregroundcomponent image in which the amount of motion blur is adjusted suppliedfrom the motion-blur adder 806 based on a selection signal reflecting auser's selection, and outputs the selected foreground component image.

As discussed above, the motion-blur adjusting unit 106 is able to adjustthe amount of motion blur based on the selection signal and the amountv′ by which motion blur is adjusted.

Also, for example, when the number of pixels corresponding to the unitof processing is 8, and the-amount of movement v is 4, as shown in FIG.85, the motion-blur adjusting unit 106 generates a matrix equationexpressed by equation (180). $\begin{matrix}{{\begin{bmatrix}4 & 3 & 2 & 1 & 0 \\3 & 4 & 3 & 2 & 1 \\2 & 3 & 4 & 3 & 2 \\1 & 2 & 3 & 4 & 3 \\0 & 1 & 2 & 3 & 4\end{bmatrix}\begin{bmatrix}{F01} \\{F02} \\{F03} \\{F04} \\{F05}\end{bmatrix}} = {v \cdot \begin{bmatrix}{\sum\limits_{i = 05}^{08}{Ci}} \\{\sum\limits_{i = 04}^{07}{Ci}} \\{\sum\limits_{i = 03}^{06}{Ci}} \\{\sum\limits_{i = 02}^{05}{Ci}} \\{\sum\limits_{i = 01}^{04}{Ci}}\end{bmatrix}}} & (180)\end{matrix}$

In this manner, the motion-blur adjusting unit 106 calculates Fi, whichis the pixel value in which the amount of motion blur is adjusted, bysetting up the equation in accordance with the length of the unit ofprocessing. Similarly, for example, when the number of pixels containedin the unit of processing is 100, the equation corresponding to 100pixels is generated so as to calculate Fi.

FIG. 86 illustrates an example of another configuration of themotion-blur adjusting unit 106. The same elements as those shown in FIG.80 are designated with like reference numerals, and an explanationthereof is thus omitted.

Based on a selection signal, a selector 821 directly supplies an inputmotion vector and a positional signal thereof to the unit-of-processingdetermining portion 801 and the model-forming portion 802.Alternatively, the selector 821 may substitute the magnitude of themotion vector by the amount v′ by which motion blur is adjusted, andthen supplies the motion vector and the positional signal thereof to theunit-of-processing determining portion 801 and the model-forming unit802.

With this arrangement, the unit-of-processing determining portion 801through the calculator 805 of the motion-blur adjusting unit 106 shownin FIG. 86 are able to adjust the amount of motion blur in accordancewith the amount of movement v and the amount v′ by which motion blur isadjusted. For example, when the amount of movement is 5, and the amountv′ by which motion blur is adjusted is 3, the unit-of-processingdetermining portion 801 through the calculator 805 of the motion-bluradjusting unit 106 shown in FIG. 86 execute computation on theforeground component image in which the amount of movement v is 5 shownin FIG. 82 according to the model shown in FIG. 84 in which the amountv′ by which motion blur is adjusted is 3. As a result, the imagecontaining motion blur having the amount of movement v of (amount ofmovement v)/(amount v′ by which motion blur is adjusted)=5/3, i.e.,about 1.7 is obtained. In this case, the calculated image does notcontain motion blur corresponding to the amount of movement v of 3.Accordingly, it should be noted that the relationship between the amountof movement v and the amount v′ by which motion blur is adjusted isdifferent from the result of the motion-blur adder 806.

As discussed above, the motion-blur adjusting unit 106 generates theequation in accordance with the amount of movement v and the unit ofprocessing, and sets the pixel values of the foreground component imagein the generated equation, thereby calculating the foreground componentimage in which the amount of motion blur is adjusted.

The processing for adjusting the amount of motion blur contained in theforeground component image executed by the motion-blur adjusting unit106 is described below with reference to the flowchart of FIG. 87.

In step S801, the unit-of-processing determining portion 801 of themotion-blur adjusting unit 106 generates the unit of processing based onthe motion vector and the area information, and supplies the generatedunit of processing to the model-forming portion 802.

In step S802, the model-forming portion 802 of the motion-blur adjustingunit 106 selects or generates the model in accordance with the amount ofmovement v and the unit of processing. In step S803, the equationgenerator 803 generates the normal equation based on the selected model.

In step S804, the adder 804 sets the pixel values of the foregroundcomponent image in the generated normal equation. In step S805, theadder 804 determines whether the pixel values of all the pixelscorresponding to the unit of processing are set. If it is determinedthat the pixel values of all the pixels corresponding to the unit ofprocessing are not yet set, the process returns to step S804, and theprocessing for setting the pixel values in the normal equation isrepeated.

If it is determined in step S805 that the pixel values of all the pixelscorresponding to the unit of processing are set, the process proceeds tostep S806. In step S806, the calculator 805 calculates the pixel valuesof the foreground in which the amount of motion blur is adjusted basedon the normal equation in which the pixel values are set supplied fromthe adder 804. The processing is then completed.

As discussed above, the motion-blur adjusting unit 106 is able to adjustthe amount of motion blur of the foreground image containing motion blurbased on the motion vector and the area information.

That is, it is possible to adjust the amount of motion blur contained inthe pixel values, that is, contained in sampled data.

As is seen from the foregoing description, the signal processor 12 shownin FIG. 4 is able to adjust the amount of motion blur contained in theinput image. The signal processor 12 configured as shown in FIG. 4 isable to calculate the mixture ratio α, which is embedded information,and outputs the calculated mixture ratio α.

FIG. 88 is a block diagram illustrating another example of theconfiguration of the motion-blur adjusting unit 106. The motion vectorand the positional information thereof supplied from the motion detector102 are supplied to a unit-of-processing determining portion 901 and anadjusting portion 905. The area information supplied from the areaspecifying unit 103 is supplied to the unit-of-processing determiningportion 901. The foreground component image supplied from theforeground/background separator 105 is supplied to a calculator 904.

The unit-of-processing determining portion 901 supplies, together withthe motion vector, the unit of processing generated based on the motionvector and the positional information thereof and the area informationto a model-forming portion 902.

The model-forming portion 902 forms a model based on the motion vectorand the input unit of processing.

An equation generator 903 generates an equation based on the modelsupplied from the model-forming portion 902.

A description is now given, with reference to the models of foregroundcomponent images shown in FIGS. 89 through 91, of an example of theequation generated by the equation generator 903 when the number offoreground components is 8, the number of pixels corresponding to theunit of processing is 12, and the amount of movement v is 5.

When the foreground components contained in the foreground componentimage corresponding to the shutter time/v are F01/v through F08/v, therelationships between F01/v through F08/v and pixel values C01 throughC12 can be expressed by equations (148) through (159), as stated above.

By considering the pixel values C12 and C11, the pixel value C12contains only the foreground component F08/v, as expressed by equation(181), and the pixel value C11 consists of the product sum of theforeground component F08/v and the foreground component F07/v.Accordingly, the foreground component F07/v can be found by equation(182).F 08/v=C 12   (181)F 07/v=C 11−C 12   (182)

Similarly, by considering the foreground components contained in thepixel values C10 through C01, the foreground components F06/v throughF01/v can be found by equations (183) through (188), respectively.F 06/v=C 10−C 11   (183)F 05/v=C 09−C 10   (184)F 04/v=C 08−C 09   (185)F 03/v=C 07−C 08+C 12   (186)F 02/v=C 06−C 07+C 11−C 12   (187)F 01/v=C 05−C 06+C 10−C 11   (188)

The equation generator 903 generates the equations for calculating theforeground components by the difference between the pixel values, asindicated by the examples of equations (181) through (188). The equationgenerator 903 supplies the generated equations to the calculator 904.

The calculator 904 sets the pixel values of the foreground componentimage in the equations supplied from the equation generator 903 so as toobtain the foreground components based on the equations in which thepixel values are set. For example, when equations (181) through (188)are supplied from the equation generator 903, the calculator 904 setsthe pixel values C05 through C12 in equations (181) through (188).

The calculator 904 calculates the foreground components based on theequations in which the pixel values are set. For example, the calculator904 calculates the foreground components F01/v through F08/v, as shownin FIG. 90, based on the calculations of equations (181) through (188)in which the pixel values C05 through C12 are set. The calculator 904supplies the foreground components F01/v through F08/v to the adjustingportion 905.

The adjusting portion 905 multiplies the foreground components suppliedfrom the calculator 904 by the amount of movement v contained in themotion vector supplied from the unit-of-processing determining portion901 so as to obtain the foreground pixel values from which motion bluris eliminated. For example, when the foreground components F01/v throughF08/v are supplied from the calculator 904, the adjusting portion 905multiples each of the foreground components F01/v through F08/v by theamount of movement v, i.e., 5, so as to obtain the foreground pixelvalues F01 through F08 from which motion blur is eliminated, as shown inFIG. 91.

The adjusting portion 905 supplies the foreground component imageconsisting of the foreground pixel values without motion blur calculatedas described above to a motion-blur adder 906 and a selector 907.

The motion-blur adder 906 is able to adjust the amount of motion blur byusing the amount v′ by which motion blur is adjusted, which is differentfrom the amount of movement v, for example, the amount v′ by whichmotion blur is adjusted, which is one half the value of the amount ofmovement v, or the amount v′ by which motion blur is adjusted, which isirrelevant to the amount of movement v. For example, as shown in FIG.84, the motion-blur adder 906 divides the foreground pixel value Fiwithout motion blur by the amount v′ by which motion blur is adjusted soas to obtain the foreground component Fi/v′. The motion-blur adder 906then calculates the sum of the foreground components Fi/v′, therebygenerating the pixel value in which the amount of motion blur isadjusted. For example, when the amount v′ by which motion blur isadjusted is 3, the pixel value C02 is set to (F01)/v′, the pixel valueC3 is set to (F01+F02)/v′, the pixel value C04 is set to(F01+F02+F03)/v′, and the pixel value C05 is set to (F02+F03+F04)/v′.

The motion-blur adder 906 supplies the foreground component image inwhich the amount of motion blur is adjusted to the selector 907.

The selector 907 selects either the foreground component image withoutmotion blur supplied from the adjusting portion 905 or the foregroundcomponent image in which the amount of motion blur is adjusted suppliedfrom the motion-blur adder 906 based on a selection signal reflecting auser's selection, and outputs the selected foreground component image.

As discussed above, the motion-blur adjusting unit 106 is able to adjustthe amount of motion blur based on the selection signal and the amountv′ by which motion blur is adjusted.

The processing for adjusting the amount of motion blur of the foregroundexecuted by the motion-blur adjusting unit 106 configured as shown inFIG. 88 is described below with reference to the flowchart of FIG. 92.

In step S901, the unit-of-processing determining portion 901 of themotion-blur adjusting unit 106 generates the unit of processing based onthe motion vector and the area information, and supplies the generatedunit of processing to the model-forming portion 902 and the adjustingportion 905.

In step S902, the model-forming portion 902 of the motion-blur adjustingunit 106 selects or generates the model according to the amount ofmovement v and the unit of processing. In step S903, the equationgenerator 903 generates, based on the selected or generated model, theequations for calculating the foreground components by the differencebetween the pixel values of the foreground component image.

In step S904, the calculator 904 sets the pixel values of the foregroundcomponent image in the generated equations, and extracts the foregroundcomponents by using the difference between the pixel values based on theequations in which the pixel values are set. In step S905, thecalculator 904 determines whether all the foreground componentscorresponding to the unit of processing have been extracted. If it isdetermined that all the foreground components corresponding to the unitof processing have not been extracted, the process returns to step S904,and the processing for extracting the foreground components is repeated.

If it is determined in step S905 that all the foreground componentscorresponding to the unit of processing have been extracted, the processproceeds to step S906. In step S906, the adjusting portion 905 adjustseach of the foreground components F01/v through F08/v supplied from thecalculator 904 based on the amount of movement v so as to obtain theforeground pixel values F01/v through F08/v from which motion blur iseliminated.

In step S907, the motion-blur adder 906 calculates the foreground pixelvalues in which the amount of motion blur is adjusted, and the selector907 selects the image without motion blur or the image in which theamount of motion blur is adjusted, and outputs the selected image. Theprocessing is then completed.

As described above, the motion-blur adjusting unit 106 configured asshown in FIG. 88 is able to more speedily adjust motion blur of theforeground image containing motion blur according to simplercomputations.

A known technique for partially eliminating motion blur, such as aWiener filter, is effective when being used in the ideal state, but isnot sufficient for an actual image quantized and containing noise. Incontrast, it is proved that the motion-blur adjusting unit 106configured as shown in FIG. 88 is sufficiently effective for an actualimage quantized and containing noise. It is thus possible to eliminatemotion blur with high precision.

FIG. 93 is a block diagram illustrating another configuration of thefunction of the signal processor 12 when the mixture-ratio calculator104 has the configuration shown in FIG. 63.

The elements similar to those shown in FIG. 4 are designated with likereference numerals, and an explanation thereof is thus omitted.

The area specifying unit 103 supplies area information to themixture-ratio calculator 104 and a synthesizer 1001. The mixture-ratiocalculator 104 supplies the mixture ratio α to the foreground/backgroundseparator 105 and the synthesizer 1001.

The foreground/background separator 105 supplies the foregroundcomponent image to the synthesizer 1001.

The synthesizer 1001 combines a certain background image with theforeground component image supplied from the foreground/backgroundseparator 105 based on the mixture ratio α supplied from themixture-ratio calculator 104 and the area information supplied from thearea specifying unit 103, and outputs the synthesized image in which thecertain background image and the foreground component image arecombined.

FIG. 94 illustrates the configuration of the synthesizer 1001. Abackground component generator 1021 generates a background componentimage based on the mixture ratio α and a certain background image, andsupplies the background component image to a mixed-area-imagesynthesizing portion 1022.

The mixed-area-image synthesizing portion 1022 combines the backgroundcomponent image supplied from the background component generator 1021with the foreground component image so as to generate a mixed-areasynthesized image, and supplies the generated mixture-area synthesizedimage to an image synthesizing portion 1023.

The image synthesizer 1023 combines the foreground component image, themixed-area synthesized image supplied from the mixed-area-imagesynthesizing portion 1022, and the certain background image based on thearea information so as to generate a synthesized image, and outputs it.

As discussed above, the synthesizer 1001 is able to combine theforeground component image with a certain background image.

The image obtained by combining a foreground component image with acertain background image based on the mixture ratio α, which is thefeature quantity, appears more natural compared to an image obtained bysimply combining pixels.

FIG. 95 is a block diagram illustrating another configuration of thefunction of the signal processor 12 when the mixture-ratio calculator104 has the configuration shown in FIG. 49.

The elements similar to those shown in FIG. 4 are designated with likereference numerals, and an explanation thereof is thus omitted.

The area specifying unit 103 supplies area information to themixture-ratio calculator 104 and a synthesizer 1001.

The mixture-ratio calculator 104 supplies the mixture ratio α to theforeground/background separator 105 and the synthesizer 1001.

The foreground/background separator 105 supplies the foregroundcomponent image to the synthesizer 1001.

The synthesizer 1001 combines a certain background image with theforeground component image supplied from the foreground/backgroundseparator 105 based on the mixture ratio α supplied from themixture-ratio calculator 104 and the area information supplied from thearea specifying unit 103, and outputs the synthesized image in which thecertain background image and the foreground component image arecombined.

FIG. 96 is a block diagram illustrating still another configuration ofthe function of the signal processor 12 for adjusting the amount ofmotion blur. The signal processor 12 shown in FIG. 4 sequentiallyperforms the area-specifying operation and the calculation for themixture ratio a. In contrast, the signal processor 12 shown in FIG. 96simultaneously performs the area-specifying operation and thecalculation for the mixture ratio a.

The functional elements similar to those in the block diagram of FIG. 4are designated with like reference numerals, and an explanation thereofis thus omitted.

An input image is supplied to a mixture-ratio calculator 1101, aforeground/background separator 1102, the area specifying unit 103, andthe object extracting unit 101.

The mixture-ratio calculator 1101 calculates, based on the input image,the estimated mixture ratio when it is assumed that each pixel containedin the input image belongs to the covered background area, and theestimated mixture ratio when it is assumed that each pixel contained inthe input image belongs to the uncovered background area, and suppliesthe estimated mixture ratios calculated as described above to theforeground/background separator 1102.

FIG. 97 is a block diagram illustrating an example of the configurationof the mixture-ratio calculator 1101 shown in FIG. 96.

An estimated-mixture-ratio processor 501 shown in FIG. 97 is the same asthe estimated-mixture-ratio processor 501 shown in FIG. 63. Anestimated-mixture-ratio processor 502 shown in FIG. 97 is the same asthe estimated-mixture-ratio processor 402 shown in FIG. 63.

The estimated-mixture-ratio processor 501 calculates the estimatedmixture ratio for each pixel by the computation corresponding to a modelof the covered background area based on the input image, and outputs thecalculated estimated mixture ratio.

The estimated-mixture-ratio processor 502 calculates the estimatedmixture ratio for each pixel by the computation corresponding to a modelof the uncovered background area based on the input image, and outputsthe calculated estimated mixture ratio.

The foreground/background separator 1102 generates the foregroundcomponent image from the input image based on the estimated mixtureratio calculated when it is assumed that the pixel belongs to thecovered background area supplied from the mixture-ratio calculator 1101,the estimated mixture ratio calculated when it is assumed that the pixelbelongs to the uncovered background area supplied from the mixture-ratiocalculator 1101, and the area information supplied from the areaspecifying unit 103, and supplies the generated foreground componentimage to the motion-blur adjusting unit 106 and the selector 107.

FIG. 98 is a block diagram illustrating an example of the configurationof the foreground/background separator 1102.

The elements similar to those of the foreground/background separator 105shown in FIG. 72 are indicated by like reference numerals, and anexplanation thereof is thus omitted.

A selector 1121 selects, based on the area information supplied from thearea specifying unit 103, either the estimated mixture ratio calculatedwhen it is assumed that the pixel belongs to the covered background areasupplied from the mixture-ratio calculator 1101 or the estimated mixtureratio calculated when it is assumed that the pixel belongs to theuncovered background area supplied from the mixture-ratio calculator1101, and supplies the selected estimated mixture ratio to theseparating portion 601 as the mixture ratio α.

The separating portion 601 extracts the foreground components and thebackground components from the pixel values of the pixels belonging tothe mixed area based on the mixture ratio α supplied from the selector1121 and the area information, and supplies the extracted foregroundcomponents to the synthesizer 603 and also supplies the foregroundcomponents to the synthesizer 605.

The separating portion 601 can be configured similarly to thecounterpart shown in FIG. 77.

The synthesizer 603 synthesizes the foreground component image andoutputs it. The synthesizer 605 synthesizes the background componentimage and outputs it.

The motion-blur adjusting unit 106 shown in FIG. 96 can be configuredsimilarly to the counterpart shown in FIG. 4. The motion-blur adjustingunit 106 adjusts the amount of motion blur contained in the foregroundcomponent image supplied from the foreground/background separator 1102based on the area information and the motion vector, and outputs theforeground component image in which the amount of motion blur isadjusted.

The selector 107 shown in FIG. 96 selects the foreground component imagesupplied from the foreground/background separator 1102 or the foregroundcomponent image in which the amount of motion blur is adjusted suppliedfrom the motion-blur adjusting unit 106 based on, for example, aselection signal reflecting a user's selection, and outputs the selectedforeground component image.

As discussed above, the signal processor 12 shown in FIG. 96 is able toadjust the amount of motion blur contained in an image corresponding toa foreground object of the input image, and outputs the resultingforeground object image. The signal processor 12 having theconfiguration shown in FIG. 96 is able to calculate the mixture ratio a,which is embedded information, and outputs the calculated mixture ratioα.

FIG. 99 is a block diagram illustrating still another configuration ofthe function of the signal processor 12 for adjusting the amount ofmotion blur. The signal processor 12 shown in FIG. 4 sequentiallyperforms the area-specifying operation and the calculation for themixture ratio α. In contrast, the signal processor 12 shown in FIG. 99simultaneously performs the area-specifying operation and thecalculation for the mixture ratio α.

The functional elements similar to those in the block diagram of FIG. 4are designated with like reference numerals, and an explanation thereofis thus omitted.

An input image is supplied to a mixture-ratio calculator 1101, aforeground/background separator 1102, the area specifying unit 103, andthe object extracting unit 101.

The mixture-ratio calculator 1101 calculates, based on the input image,the estimated mixture ratio when it is assumed that each pixel containedin the input image belongs to the covered background area, and theestimated mixture ratio when it is assumed that each pixel contained inthe input image belongs to the uncovered background area, and suppliesthe estimated mixture ratios calculated as described above to theforeground/background separator 1102.

FIG. 100 is a block diagram illustrating an example of the configurationof the mixture-ratio calculator 1101 shown in FIG. 99.

An estimated-mixture-ratio processor 401 shown in FIG. 100 is the sameas the estimated-mixture-ratio processor 401 shown in FIG. 49. Anestimated-mixture-ratio processor 402 shown in FIG. 100 is the same asthe estimated-mixture-ratio processor 402 shown in FIG. 49.

The estimated-mixture-ratio processor 401 calculates the estimatedmixture ratio for each pixel by the computation corresponding to a modelof the covered background area based on the input image, and outputs thecalculated estimated mixture ratio.

The estimated-mixture-ratio processor 402 calculates the estimatedmixture ratio for each pixel by the computation corresponding to a modelof the uncovered background area based on the input image, and outputsthe calculated estimated mixture ratio.

The foreground/background separator 1102 generates the foregroundcomponent image from the input image based on the estimated mixtureratio calculated when it is assumed that the pixel belongs to thecovered background area supplied from the mixture-ratio calculator 1101,the estimated mixture ratio calculated when it is assumed that the pixelbelongs to the uncovered background area supplied from the mixture-ratiocalculator 1101, and the area information supplied from the areaspecifying unit 103, and supplies the generated foreground componentimage to the motion-blur adjusting unit 106 and the selector 107.

The motion-blur adjusting unit 106 shown in FIG. 99 can be configuredsimilarly to the counterpart shown in FIG. 4. The motion-blur adjustingunit 106 adjusts the amount of motion blur contained in the foregroundcomponent image supplied from the foreground/background separator 1102based on the area information and the motion vector, and outputs theforeground component image in which the amount of motion blur isadjusted.

The selector 107 shown in FIG. 99 selects the foreground component imagesupplied from the foreground/background separator 1102 or the foregroundcomponent image in which the amount of motion blur is adjusted suppliedfrom the motion-blur adjusting unit 106 based on, for example, aselection signal reflecting a user's selection, and outputs the selectedforeground component image.

As discussed above, the signal processor 12 shown in FIG. 99 is able toadjust the amount of motion blur contained in an image corresponding toa foreground object of the input image, and outputs the resultingforeground object image. The signal processor 12 having theconfiguration shown in FIG. 99 is able to calculate the mixture ratio a,which is embedded information, and outputs the calculated mixture ratioa.

FIG. 101 is a block diagram illustrating another configuration of thefunction of the signal processor 12 for combining a foreground componentimage with a certain background image. The signal processor 12 shown inFIG. 93 serially performs the area-specifying operation and thecalculation for the mixture ratio α. In contrast, the signal processor12 shown in FIG. 101 performs the area-specifying operation and thecalculation for the mixture ratio α in a parallel manner.

The functional elements similar to those indicated by the block of FIG.96 are indicated by like reference numerals, and an explanation thereofis thus omitted.

The mixture-ratio calculator 1101 shown in FIG. 101 calculates, based onthe input image, the estimated mixture ratio when it is assumed thateach pixel contained in the input image belongs to the coveredbackground area, and the estimated mixture ratio when it is assumed thateach pixel contained in the input image belongs to the uncoveredbackground area, and supplies the estimated mixture ratios calculated asdescribed above to the foreground/background separator 1102 and asynthesizer 1201.

The mixture-ratio calculator 1101 shown in FIG. 101 can be configured asshown in FIG. 97.

The foreground/background separator 1102 shown in FIG. 101 generates theforeground component image from the input image based on the estimatedmixture ratio calculated when it is assumed that the pixel belongs tothe covered background area supplied from the mixture-ratio calculator1101, the estimated mixture ratio calculated when it is assumed that thepixel belongs to the uncovered background area supplied from themixture-ratio calculator 1101, and the area information supplied fromthe area specifying unit 103, and supplies the generated foregroundcomponent image to the synthesizer 1201.

The synthesizer 1201 combines a certain background image with theforeground component image supplied from the foreground/backgroundseparator 1102 based on the estimated mixture ratio calculated when itis assumed that the pixel belongs to the covered background areasupplied from the mixture-ratio calculator 1101, the estimated mixtureratio calculated when it is assumed that the pixel belongs to theuncovered background area supplied from the mixture-ratio calculator1101, and the area information supplied from the area specifying unit103, and outputs the synthesized image in which the background image andthe foreground component image are combined.

FIG. 102 illustrates the configuration of the synthesizer 1201. Thefunctional elements similar to those of the block diagram of FIG. 94 aredesignated with like reference numerals, and explanation thereof is thusomitted.

A selector 1221 selects, based on the area information supplied from thearea specifying unit 103, either the estimated mixture ratio calculatedwhen it is assumed that the pixel belongs to the covered background areasupplied from the mixture-ratio calculator 1101 or the estimated mixtureratio calculated when it is assumed that the pixel belongs to theuncovered background area supplied from the mixture-ratio calculator1101, and supplies the selected estimated mixture ratio to thebackground component generator 1021 as the mixture ratio a.

The background component generator 1021 shown in FIG. 102 generates abackground component image based on the mixture ratio α supplied fromthe selector 1221 and a certain background image, and supplies thebackground component image to the mixed-area-image synthesizing portion1022.

The mixed-area-image synthesizing portion 1022 shown in FIG. 102combines the background component image supplied from the backgroundcomponent generator 1021 with the foreground component image so as togenerate a mixed-area synthesized image, and supplies the generatedmixed-area synthesized image to the image synthesizing portion 1023.

The image synthesizing portion 1023 combines the foreground componentimage, the mixed-area synthesized image supplied from themixed-area-image synthesizing portion 1022, and the background imagebased on the area information so as to generate a synthesized image andoutputs it.

In this manner, the synthesizer 1201 is able to combine the foregroundcomponent image with a certain background image.

FIG. 103 is a block diagram illustrating another configuration of thefunction of the signal processor 12 for combining a foreground componentimage with a certain background image. The signal processor 12 shown inFIG. 95 serially performs the area-specifying operation and thecalculation for the mixture ratio α. In contrast, the signal processor12 shown in FIG. 103 performs the area-specifying operation and thecalculation for the mixture ratio α in a parallel manner.

The functional elements similar to those indicated by the block of FIG.99 are indicated by like reference numerals, and an explanation thereofis thus omitted.

The mixture-ratio calculator 1101 shown in FIG. 103 calculates, based onthe input image, the estimated mixture ratio when it is assumed thateach pixel contained in the input image belongs to the coveredbackground area, and the estimated mixture ratio when it is assumed thateach pixel contained in the input image belongs to the uncoveredbackground area, and supplies the estimated mixture ratios calculated asdescribed above to the foreground/background separator 1102 and asynthesizer 1201.

The mixture-ratio calculator 1101 shown in FIG. 103 can be configured asshown in FIG. 100.

The foreground/background separator 1102 shown in FIG. 103 generates theforeground component image from the input image based on the estimatedmixture ratio calculated when it is assumed that the pixel belongs tothe covered background area supplied from the mixture-ratio calculator1101, the estimated mixture ratio calculated when it is assumed that thepixel belongs to the uncovered background area supplied from themixture-ratio calculator 1101, and the area information supplied fromthe area specifying unit 103, and supplies the generated foregroundcomponent image to the synthesizer 1201.

The synthesizer 1201 combines a certain background image with theforeground component image supplied from the foreground/backgroundseparator 1102 based on the estimated mixture ratio calculated when itis assumed that the pixel belongs to the covered background areasupplied from the mixture-ratio calculator 1101, the estimated mixtureratio calculated when it is assumed that the pixel belongs to theuncovered background area supplied from the mixture-ratio calculator1101, and the area information supplied from the area specifying unit103, and outputs the synthesized image in which the background image andthe foreground component image are combined.

As described above, according to the present invention, the mixtureratio indicating the mixture state of a plurality of objects, such as abackground object and a moving object image, can be detected.

The embodiment has been discussed above by setting the mixture ratio αto the ratio of the background components contained in the pixel values.However, the mixture ratio α may be set to the ratio of the foregroundcomponents contained in the pixel values.

The embodiment has been discussed above by setting the moving directionof the foreground object to the direction from the left to the right.However, the moving direction is not restricted to the above-describeddirection.

In the above description, a real-space image having a three-dimensionalspace and time axis information is projected onto a time space having atwo-dimensional space and time axis information by using a video camera.However, the present invention is not restricted to this example, andcan be applied to the following case. When a greater amount of firstinformation in one-dimensional space is projected onto a smaller amountof second information in a two-dimensional space, distortion generatedby the projection can be corrected, significant information can beextracted, or a more natural image can be synthesized.

The sensor 11 is not restricted to a CCD, and may be another type ofsensor, such as a solid-state image-capturing device, for example, a BBD(Bucket Brigade Device), a CID (Charge Injection Device), or a CPD(Charge Priming Device), or a CMOS (Complementary Metal OxideSemiconductor). Also, the sensor does not have to be a sensor in whichdetection devices are arranged in a matrix, and may be a sensor in whichdetection devices are arranged in one line.

A recording medium in which a program for performing the signalprocessing of the present invention is recorded may be formed of apackage medium in which the program is recorded, which is distributedfor providing the program to a user separately from the computer, asshown in FIG. 3, such as the magnetic disk 51 (including a floppy(registered trade name) disk), the optical disc 52 (CD-ROM (CompactDisc-Read Only Memory) and a DVD (Digital Versatile Disc)), themagneto-optical disk 53 (including MD (Mini-Disc) (registered tradename)), or the semiconductor memory 54. The recording medium may also beformed of the ROM 22 or a hard disk contained in the storage unit 28 inwhich the program is recorded, such recording medium being provided tothe user while being prestored in the computer.

The steps forming the program recorded in a recording medium may beexecuted chronologically according to the orders described in thespecification. However, they do not have to be executed in a time-seriesmanner, and they may be executed concurrently or individually.

INDUSTRIAL APPLICABILITY

According to the first invention, the mixture ratio indicating themixture state of a plurality of objects, such as a background image anda moving object image, can be detected.

According to the second invention, the mixture ratio indicating themixture state of a plurality of objects, such as a background image anda moving object image, can be detected.

1. An image processing apparatus for processing image data which isformed of a predetermined number of pixel data obtained by animage-capturing device including a predetermined number of pixels, thepixels having a time integrating function, said image processingapparatus comprising: relational-expression generating means forextracting, in correspondence with a designated pixel of a designatedframe of the image data, mixed pixel data, which is the pixel data, inwhich a plurality of objects contained in the image data are mixed, fromthe designated frame and a peripheral frame around the designated framein accordance with a motion of a foreground object which forms aforeground of the plurality of objects, and also for extracting, incorrespondence with the mixed pixel data, background pixel data, whichis the pixel data, corresponding to a background object which forms abackground of the plurality of objects, the background pixel data beingassociated with the corresponding mixed pixel data, from a framedifferent from the frames from which the mixed pixel data are extractedin accordance with a motion of the background object so as to generate aplurality of relational expressions indicating relationships between themixed pixel data and the background pixel data concerning the designatedpixel; and mixture-ratio detection means for detecting a mixture ratioindicating a mixture state of the plurality of objects in the real worldconcerning the designated pixel based on the relational expressions,wherein said relational-expression generating means generates theplurality of relational expressions based on a first approximation inwhich components of the foreground object contained in the mixed pixeldata change substantially linearly with respect to the positions of thepixels, and a second approximation in which the mixture ratio of themixed pixel data extracted from the designated frame changessubstantially linearly with respect to the positions of the pixels. 2.An image processing apparatus according to claim 1, further comprisingforeground/background separation means for separating the image datainto a foreground object image consisting of only the foreground objectcomponents which form the foreground object in the image data and abackground object image consisting of only background object componentswhich form the background object in the image data based on the mixtureratio corresponding to the designated pixel.
 3. An image processingapparatus according to claim 1, wherein said mixture-ratio detectionmeans detects the mixture ratio by solving the plurality of relationalexpressions according to a method of least squares.
 4. An imageprocessing method for processing image data which is formed of apredetermined number of pixel data obtained by an image-capturing deviceincluding a predetermined number of pixels, the pixels having a timeintegrating function, said image processing apparatus comprising: arelational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of the image data, mixedpixel data, which is the pixel data, in which a plurality of objectscontained in the image data are mixed, from the designated frame and aperipheral frame around the designated frame in accordance with a motionof a foreground object which forms a foreground of the plurality ofobjects, and also of extracting, in correspondence with the mixed pixeldata, background pixel data, which is the pixel data, corresponding to abackground object which forms a background of the plurality of objects,the background pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject, so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and a mixture-ratiodetection step of detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions, wherein in saidrelational-expression generating step, the plurality of relationalexpressions are generated based on a first approximation in whichcomponents of the foreground object contained in the mixed pixel datachange substantially linearly with respect to the positions of thepixels, and a second approximation in which the mixture ratio of themixed pixel data extracted from the designated frame changessubstantially linear with respect to the positions of the pixels.
 5. Animage processing method according to claim 4, further comprising aforeground/background separation step of separating the image data intoa foreground object image consisting of only the foreground objectcomponents which form the foreground object in the image data and abackground object image consisting of only background object componentswhich form the background object in the image data based on the mixtureratio corresponding to the designated pixel.
 6. An image processingmethod according to claim 4, wherein in said mixture-ratio detectionstep, the mixture ratio is detected by solving the plurality ofrelational expressions according to a method of least squares.
 7. Arecording medium in which a computer-readable program is recorded, saidprogram being used for processing image data which is formed of apredetermined number of pixel data obtained by an image-capturing deviceincluding a predetermined number of pixels, the pixels having a timeintegrating function, said program comprising: a relational-expressiongenerating step of extracting, in correspondence with a designated pixelof a designated frame of the image data, mixed pixel data, which is thepixel data, in which a plurality of objects contained in the image dataare mixed, from the designated frame and a peripheral frame around thedesignated frame in accordance with a motion of a foreground objectwhich forms a foreground of the plurality of objects, and also ofextracting, in correspondence with the mixed pixel data, backgroundpixel data, which is the pixel data, corresponding to a backgroundobject which forms a background of the plurality of objects, thebackground pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject, so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and a mixture-ratiodetection step of detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions, wherein in saidrelational-expression generating step, the plurality of relationalexpressions are generated based on a first approximation in whichcomponents of the foreground object contained in the mixed pixel datachange substantially linearly with respect to the positions of thepixels, and a second approximation in which the mixture ratio of themixed pixel data extracted from the designated frame changessubstantially linear with respect to the positions of the pixels.
 8. Arecording medium according to claim 7, wherein said program furthercomprises a foreground/background separation step of separating theimage data into a foreground object image consisting of only theforeground object components which form the foreground object in theimage data and a background object image consisting of only backgroundobject components which form the background object in the image databased on the mixture ratio corresponding to the designated pixel.
 9. Arecording medium according to claim 7, wherein in said mixture-ratiodetection step, the mixture ratio is detected by solving the pluralityof relational expressions according to a method of least squares.
 10. Aprogram for allowing a computer for processing image data which isformed of a predetermined number of pixel data obtained by animage-capturing device including a predetermined number of pixels, thepixels having a time integrating function, to execute: arelational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of the image data, mixedpixel data, which is the pixel data, in which a plurality of objectscontained in the image data are mixed, from the designated frame and aperipheral frame around the designated frame in accordance with a motionof a foreground object which forms a foreground of the plurality ofobjects, and also of extracting, in correspondence with the mixed pixeldata, background pixel data, which is the pixel data, corresponding to abackground object which forms a background of the plurality of objects,the background pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and a mixture-ratiodetection step of detecting a mixture ratio indicating a mixture stateof the plurality of objects in the real world concerning the designatedpixel based on the relational expressions, wherein in saidrelational-expression generating step, the plurality of relationalexpressions are generated based on a first approximation in whichcomponents of the foreground object contained in the mixed pixel datachange substantially linearly with respect to the positions of thepixels, and a second approximation in which the mixture ratio of themixed pixel data extracted from the designated frame changessubstantially linear with respect to the positions of the-pixels.
 11. Aprogram according to claim 10, further comprising aforeground/background separation step of separating the image data intoa foreground object image consisting of only the foreground objectcomponents which form the foreground object in the image data and abackground object image consisting of only background object componentswhich form the background object in the image data based on the mixtureratio corresponding to the designated pixel.
 12. A program according toclaim 10, wherein in said mixture-ratio detection step, the mixtureratio is detected by solving the plurality of relational expressionsaccording to a method of least squares.
 13. An image-capturing apparatuscomprising: image-capturing means for outputting a subject imagecaptured by an image-capturing device including a predetermined numberof pixels having a time integrating function as image data consisting ofa predetermined number of pixel data; relational-expression generatingmeans for extracting, in correspondence with a designated pixel of adesignated frame of the image data, mixed pixel data, which is the pixeldata, in which a plurality of objects contained in the image data aremixed, from the designated frame and a peripheral frame around thedesignated frame in accordance with a motion of a foreground objectwhich forms a foreground of the plurality of objects, and also forextracting, in correspondence with the mixed pixel data, backgroundpixel data, which is the pixel data, corresponding to a backgroundobject which forms a background of the plurality of objects, thebackground pixel data being associated with the corresponding mixedpixel data, from a frame different from the frames from which the mixedpixel data are extracted in accordance with a motion of the backgroundobject so as to generate a plurality of relational expressionsindicating relationships between the mixed pixel data and the backgroundpixel data concerning the designated pixel; and mixture-ratio detectionmeans for detecting a mixture ratio indicating a mixture state of theplurality of objects in the real world concerning the designated pixelbased on the relational expressions, wherein said relational-expressiongenerating means generates the plurality of relational expressions basedon a first approximation in which components of the foreground objectcontained in the mixed pixel data change substantially linearly withrespect to the positions of the pixels, and a second approximation inwhich the mixture ratio of the mixed pixel data extracted from thedesignated frame changes substantially linearly with respect to thepositions of the pixels.
 14. An image-capturing apparatus according toclaim 13, further comprising foreground/background separation means forseparating the image data into a foreground object image consisting ofonly the foreground object components which form the foreground objectin the image data and a background object image consisting of onlybackground object components which form the background object in theimage data based on the mixture ratio corresponding to the designatedpixel.
 15. An image-capturing apparatus according to claim 13, whereinsaid mixture-ratio detection means detects the mixture ratio by solvingthe plurality of relational expressions according to a method of leastsquares.
 16. An image processing apparatus for processing image datawhich is formed of a predetermined number of pixel data obtained by animage-capturing device including a predetermined number of pixels, thepixels having a time integrating function, said image processingapparatus comprising: relational-expression generating means forextracting, in correspondence with a designated pixel of a designatedframe of the image data, pixel data of a peripheral frame around thedesignated frame as background pixel data corresponding to a backgroundobject of a plurality of objects of the image data, and also forextracting designated pixel data of the designated pixel and proximitypixel data of a pixel located in close proximity with the designatedpixel in the designated frame so as to generate a plurality ofrelational expressions indicating relationships of the designated pixeldata, the proximity pixel data, and the background pixel datacorresponding to the designated pixel data or the proximity pixel dataconcerning the designated pixel; and mixture-ratio detection means fordetecting a mixture ratio indicating a mixture state of the plurality ofobjects in the real world concerning the designated pixel based on therelational expressions, wherein said relational-expression generatingmeans generates the plurality of relational expressions based on anapproximation in which the mixture ratio corresponding to the designatedpixel and the proximity pixel is uniform.
 17. An image processingapparatus according to claim 16, wherein said relational-expressiongenerating means generates the plurality of relational expressions basedon an approximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data are uniform.
 18. An image processing apparatusaccording to claim 16, wherein said relational-expression generatingmeans generates the plurality of relational expressions based on anapproximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data change substantially linearly with respect to thepositions of the pixels.
 19. An image processing apparatus according toclaim 16, further comprising foreground/background separation means forseparating the image data into a foreground object image consisting ofonly the foreground object components which form the foreground objectin the image data and a background object image consisting of onlybackground object components which form the background object in theimage data based on the mixture ratio corresponding to the designatedpixel.
 20. An image processing apparatus according to claim 16, whereinsaid mixture-ratio detection means detects the mixture ratio by solvingthe plurality of relational expressions according to a method of leastsquares.
 21. An image processing method for processing image data whichis formed of a predetermined number of pixel data obtained by animage-capturing device including a predetermined number of pixels, thepixels having a time integrating function, said image processing methodcomprising: a relational-expression generating step of extracting, incorrespondence with a designated pixel of a designated frame of theimage data, pixel data of a peripheral frame around the designated frameas background pixel data corresponding to a background object of aplurality of objects of the image data, and also of extractingdesignated pixel data of the designated pixel and proximity pixel dataof a pixel located in close proximity with the designated pixel in thedesignated frame so as to generate a plurality of relational expressionsindicating relationships of the designated pixel data, the-proximitypixel data, and the background pixel data corresponding to thedesignated pixel data or the proximity pixel data concerning thedesignated pixel; and a mixture-ratio detection step of detecting amixture ratio indicating a mixture state of the plurality of objects inthe real world concerning the designated pixel based on the relationalexpressions, wherein in said relational-expression generating step, theplurality of relational expressions are generated based on anapproximation in which the mixture ratio corresponding to the designatedpixel and the proximity pixel is uniform.
 22. An image processing methodaccording to claim 21, wherein in said relational-expression generatingstep, the plurality of relational expressions are generated based on anapproximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data are uniform.
 23. An image processing methodaccording to claim 21, wherein in said relational-expression generatingstep, the plurality of relational expressions are generated based on anapproximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data change substantially linearly with respect to thepositions of the pixels.
 24. An image processing method according toclaim 21, further comprising a foreground/background separation step ofseparating the image data into a foreground object image consisting ofonly the foreground object components which form the foreground objectin the image data and a background object image consisting of onlybackground object components which form the background object in theimage data based on the mixture ratio corresponding to the designatedpixel.
 25. An image processing method according to claim 21, wherein insaid mixture-ratio detection step, the mixture ratio is detected bysolving the plurality of relational expressions according to a method ofleast squares.
 26. A recording medium in which a computer-readableprogram is recorded, said program being used for processing image datawhich is formed of a predetermined number of pixel data obtained by animage-capturing device including a predetermined number of pixels, thepixels having a time integrating function, said program comprising: arelational-expression generating step of extracting, in correspondencewith a designated pixel of a designated frame of the image data, pixeldata of a peripheral frame around the designated frame as backgroundpixel data corresponding to a background object of a plurality ofobjects of the image data, and also of extracting designated pixel dataof the designated pixel and proximity pixel data of a pixel located inclose proximity with the designated pixel in the designated frame so asto generate a plurality of relational expressions indicatingrelationships of the designated pixel data, the proximity pixel data,and the background pixel data corresponding to the designated pixel dataor the proximity pixel data concerning the designated pixel; and amixture-ratio detection step of detecting a mixture ratio indicating amixture state of the plurality of objects in the real world concerningthe designated pixel based on the relational expressions, wherein insaid relational-expression generating step, the plurality of relationalexpressions are generated based on an approximation in which the mixtureratio corresponding to the designated pixel and the proximity pixel isuniform.
 27. A recording medium according to claim 26, wherein in saidrelational-expression generating step, the plurality of relationalexpressions are generated based on an approximation in which componentsof a foreground object of the plurality of objects contained in thedesignated pixel data and the proximity pixel data are uniform.
 28. Arecording medium according to claim 26, wherein in saidrelational-expression generating step, the plurality of relationalexpressions are generated based on an approximation in which componentsof a foreground object of the plurality of objects contained in thedesignated pixel data and the proximity pixel data change substantiallylinearly with respect to the positions of the pixels.
 29. A recordingmedium according to claim 26, wherein said program comprises aforeground/background separation step of separating the image data intoa foreground object image consisting of only the foreground objectcomponents which form the foreground object in the image data and abackground object image consisting of only background object componentswhich form the background object in the image data based on the mixtureratio corresponding to the designated pixel.
 30. A recording mediumaccording to claim 26, wherein in said mixture-ratio detection step, themixture ratio is detected by solving the plurality of relationalexpressions according to a method of least squares.
 31. A program forallowing a computer for processing image data which is formed of apredetermined number of pixel data obtained by an image-capturing deviceincluding a predetermined number of pixels, the pixels having a timeintegrating function, to execute: a relational-expression generatingstep of extracting, in correspondence with a designated pixel of adesignated frame of the image data, pixel data of a peripheral framearound the designated frame as background pixel data corresponding to abackground object of a plurality of objects of the image data, and alsoof extracting designated pixel data of the designated pixel andproximity pixel data of a pixel located in close proximity with thedesignated pixel in the designated frame so as to generate a pluralityof relational expressions indicating relationships of the designatedpixel data, the proximity pixel data, and the background pixel datacorresponding to the designated pixel data or the proximity pixel dataconcerning the designated pixel; and a mixture-ratio detection step ofdetecting a mixture ratio indicating a mixture state of the plurality ofobjects in the real world concerning the designated pixel based on therelational expressions, wherein in said relational-expression generatingstep, the plurality of relational expressions are generated based on anapproximation in which the mixture ratio corresponding to the designatedpixel and the proximity pixel is uniform.
 32. A program according toclaim 31, wherein in said relational-expression generating step, theplurality of relational expressions are generated based on anapproximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data are uniform.
 33. A program according to claim 31,wherein in said relational-expression generating step, the plurality ofrelational expressions are generated based on an approximation in whichcomponents of a foreground object of the plurality of objects containedin the designated pixel data and the proximity pixel data changesubstantially linearly with respect to the positions of the pixels. 34.A program according to claim 31, further comprising aforeground/background separation step of separating the image data intoa foreground object image consisting of only the foreground objectcomponents which form the foreground object in the image data and abackground object image consisting of only background object componentswhich form the background object in the image data based on the mixtureratio corresponding to the designated pixel.
 35. A program according toclaim 31, wherein in said mixture-ratio detection step, the mixtureratio is detected by solving the plurality of relational expressionsaccording to a method of least squares.
 36. An image-capturing apparatuscomprising: image-capturing means for outputting a subject imagecaptured by an image-capturing device including a predetermined numberof pixels having a time integrating function as image data consisting ofa predetermined number of pixel data; relational-expression generatingmeans for extracting, in correspondence with a designated pixel of adesignated frame of the image data, pixel data of a peripheral framearound the designated frame as background pixel data corresponding to abackground object of a plurality of objects of the image data, and alsofor extracting designated pixel data of the designated pixel andproximity pixel data of a pixel located in close proximity with thedesignated pixel in the designated frame so as to generate a pluralityof relational expressions indicating relationships of the designatedpixel data, the proximity pixel data, and the background pixel datacorresponding to the designated pixel data or the proximity pixel dataconcerning the designated pixel; and mixture-ratio detection means fordetecting a mixture ratio indicating a mixture state of the plurality ofobjects in the real world concerning the designated pixel based on therelational expressions, wherein said relational-expression generatingmeans generates the plurality of relational expressions based on anapproximation in which the mixture ratio corresponding to the designatedpixel and the proximity pixel is uniform.
 37. An image-capturingapparatus according to claim 36, wherein said relational-expressiongenerating means generates the plurality of relational expressions basedon an approximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data are uniform.
 38. An image-capturing apparatusaccording to claim 36, wherein said relational-expression generatingmeans generates the plurality of relational expressions based on anapproximation in which components of a foreground object of theplurality of objects contained in the designated pixel data and theproximity pixel data change substantially linearly with respect to thepositions of the pixels.
 39. An image-capturing apparatus according toclaim 36, further comprising foreground/background separation means forseparating the image data into a foreground object image consisting ofonly the foreground object components which form the foreground objectin the image data and a background object image consisting of onlybackground object components which form the background object in theimage data based on the mixture ratio corresponding to the designatedpixel.
 40. An image-capturing apparatus according to claim 36, whereinsaid mixture-ratio detection means detects the mixture ratio by solvingthe plurality of relational expressions according to a method of leastsquares.